Conversational AI Agents Developer Job at Sybrant Technologies

Senior Agentic AI Developer

Senior Agentic AI Developer to build production-grade autonomous agents and orch...

Location

United States , San Francisco

Salary:

156000.00 - 234000.00 USD / Year

GoFundMe

Expiration Date

Until further notice

Requirements

6+ years in software engineering, with 3+ years hands-on building production-grade AI/ML systems
Deep expertise in LLM agent frameworks (LangGraph, Google ADK, CrewAI, AutoGen, Pydantic AI, LangChain)
Proven ability to architect agentic systems from scratch, including planning/reasoning flows and multi-agent orchestration
Strong Python/TypeScript skills and experience in microservices and distributed infrastructure
Familiarity with vector databases (e.g., Pinecone, ChromaDB), knowledge graphs (Neo4j, Graphiti), and RAG pipelines
Deep autonomous agent architecture knowledge including advanced reasoning, planning, task decomposition, multi-step automation, tool-use patterns, evaluation systems beyond simple response generation
Enterprise integration expertise with RESTful APIs, A2A interoperability, webhook systems, Model Context Protocol (MCP) tools for dynamic tool discovery
Production experience with cloud-native infrastructure (Docker, Kubernetes, AWS/GCP)
Demonstrated experience with reinforcement learning, agent optimization, and agent evaluation techniques
Strong understanding of agent safety, bias mitigation, transparency, and ethical design practices

Job Responsibility

Design and implement LLM-based autonomous agents that perform beyond simple responses — including planning, reasoning, tool-use, and long-term task decomposition
Engineer context- and memory-rich agents that integrate structured data, external APIs, and conversational context to optimize outcomes
Build production-scale orchestration frameworks using tools such as LangGraph, Pydantic AI, Google ADK, and CrewAI to orchestrate complex workflows across campaign creation, optimization, and tracking in distributed microservices architectures
Implement agent-to-agent (A2A) communication protocols using Model Context Protocol (MCP), enabling tool discovery and dynamic peer -to-peer task delegation between specialized agents in our fundraising ecosystem
Develop microservice-based, cloud-native infrastructure for autonomous agent deployment with Docker/Kubernetes, observability tooling, and cloud platforms (AWS/GCP)
Ensure enterprise-grade performance, monitoring, and fault tolerance in agent systems supporting large-scale fundraising workflows
Design sophisticated prompt strategies, agent memory architectures, vector and graph database implementations for maintaining context across multi-turn conversations and long-running campaign lifecycles
Architect and optimize vector and graph database integrations (e.g., Pinecone, Weaviate, ChromaDB) for agent memory and semantic recall
Build custom agentic frameworks for use cases across campaign storytelling, optimization, and donor engagement
Architect frameworks from scratch tailored to fundraising domain challenges, incorporating advanced tool-use capabilities that integrate with platform APIs, knowledge graphs, and external systems

What we offer

Make an Impact: Be part of a mission-driven organization making a positive difference in millions of lives every year
Innovative Environment: Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere
Collaborative Team: Join a fun and collaborative team that works hard and celebrates success together
Competitive Benefits: Enjoy competitive pay and comprehensive healthcare benefits
Holistic Support: Enjoy financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being
Growth Opportunities: Participate in learning, development, and recognition programs to help you thrive and grow
Commitment to DEI: Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups
Community Engagement: Make a difference through our volunteering program

Fulltime

Senior Agentic AI Developer

Build production-grade autonomous agents and orchestration systems that reshape ...

Location

Argentina , Buenos Aires

Salary:

Not provided

GoFundMe

Expiration Date

Until further notice

Requirements

6+ years in software engineering
3+ years hands-on building production-grade AI/ML systems
Deep expertise in LLM agent frameworks (LangGraph, Google ADK, CrewAI, AutoGen, Pydantic AI, LangChain)
Proven ability to architect agentic systems from scratch, including planning/reasoning flows and multi-agent orchestration
Strong Python/TypeScript skills and experience in microservices and distributed infrastructure
Familiarity with vector databases (e.g., Pinecone, ChromaDB), knowledge graphs (Neo4j, Graphiti), and RAG pipelines
Deep autonomous agent architecture knowledge including advanced reasoning, planning, task decomposition, multi-step automation, tool-use patterns, evaluation systems beyond simple response generation
Enterprise integration expertise with RESTful APIs, A2A interoperability, webhook systems, Model Context Protocol (MCP) tools for dynamic tool discovery
Production experience with cloud-native infrastructure (Docker, Kubernetes, AWS/GCP)
Demonstrated experience with reinforcement learning, agent optimization, and agent evaluation techniques

Job Responsibility

Design and implement LLM-based autonomous agents that perform beyond simple responses — including planning, reasoning, tool-use, and long-term task decomposition
Engineer context- and memory-rich agents that integrate structured data, external APIs, and conversational context to optimize outcomes
Build production-scale orchestration frameworks using tools such as LangGraph, Pydantic AI, Google ADK, and CrewAI to orchestrate complex workflows across campaign creation, optimization, and tracking in distributed microservices architectures
Implement agent-to-agent (A2A) communication protocols using Model Context Protocol (MCP), enabling tool discovery and dynamic peer -to-peer task delegation between specialized agents in our fundraising ecosystem
Develop microservice-based, cloud-native infrastructure for autonomous agent deployment with Docker/Kubernetes, observability tooling, and cloud platforms (AWS/GCP)
Ensure enterprise-grade performance, monitoring, and fault tolerance in agent systems supporting large-scale fundraising workflows
Design sophisticated prompt strategies, agent memory architectures, vector and graph database implementations for maintaining context across multi-turn conversations and long-running campaign lifecycles
Architect and optimize vector and graph database integrations (e.g., Pinecone, Weaviate, ChromaDB) for agent memory and semantic recall
Build custom agentic frameworks for use cases across campaign storytelling, optimization, and donor engagement
Architect frameworks from scratch tailored to fundraising domain challenges, incorporating advanced tool-use capabilities that integrate with platform APIs, knowledge graphs, and external systems

What we offer

Competitive pay
Comprehensive healthcare benefits
Financial assistance for things like hybrid work, family planning
Generous parental leave
Flexible time-off policies
Mental health and wellness resources
Learning, development, and recognition programs

AI Conversation Design Specialist

This role is focused on creating a Conversational AI-driven self-service experie...

Location

Munich; Berlin; Dublin

Salary:

Not provided

Personio SE & Co. KG

Expiration Date

Until further notice

Requirements

4–6 years of experience delivering AI Agents or chatbots (voice, chat, email, and messaging) preferably in SaaS, technology, or customer experience
German fluency highly preferred
Hands-on experience with chatbots / AI copilots such as Intercom Fin, Decagon, MavenAGI, Ada, Forethought or equivalent
Familiarity with APIs, comfortable occasionally writing snippets of code to bring in data from other systems into Intercom Fin
Strong understanding of AI/ML concepts, natural language processing, and customer support technologies (e.g., chatbots, virtual assistants)
Experience working with data analytics tools and interpreting model performance metrics
Demonstrated ability to translate business needs and customer pain points into technical requirements for AI solutions
Experience collaborating with Product, Engineering, Data, Systems, Customer Support, and Professional Services teams
Knowledge of customer experience metrics (CSAT, NPS, etc.) and best practices in B2B SaaS
Strong project management skills, including Agile or similar methodologies

Job Responsibility

Self-Service and Productivity Outcomes: Drive contact volume reduction and self-service by implementing solutions for top contact drivers, as well as driving Support Agent productivity and handling time through improvements to co-pilots
AI Conversation Automation: Develop AI automated workflows / agent operating procedures, run batch tests, configure personalized answers, and reverse engineer unresolved conversations
Conversation Design: Architect natural, useful interactions between customers and AI chatbots. Design the flow and logic of conversations for the chatbots, partnering with subject-matter experts. You tune and design bot conversations —flows, intents/tagging, prompts/responses, fallback logic— to cut hallucinations, misroutes, and unnecessary handoffs
AI Service Journey Design: Define and govern AI↔human and AI↔AI handoffs (confidence thresholds, triggers, routing rules), ensuring brand voice, privacy, and responsible-AI standards, building a deep knowledge of our customer journeys and user stories to anticipate and design for different scenarios
Data Integration: bring data from 3rd party systems and our own product into Intercom Fin to improve AI conversation effectiveness
Performance Monitoring and Improvement: Track key metrics (e.g., self-serve resolutions, monthly active users, deflection rates, resolution time, customer experience score, NPS) to evaluate AI impact, identify gaps, and implement improvements
AI Solution Delivery: Lead the implementation of AI-powered tools (e.g., chatbots, copilots, virtual assistants) that address common customer pain points and streamline support and professional services processes, and partner with Engineering and Systems on integrations and fixes
Cross-Functional Collaboration: Work closely with Product, Engineering, Customer Experience, Data and Systems teams to ensure AI solutions are aligned with customer needs and business objectives, and that we integrate seamlessly with the Personio Assistant and internal support tooling
Continuous Quality Improvement: Oversee the ongoing quality fine-tuning of AI tools using real customer data and feedback to improve routing, accuracy, relevance, and customer satisfaction. You approach with a product mindset, anticipating edge cases and interaction effects, and regression test as new changes are introduced. You monitor bot/service health, triage incidents and misroutes, and coordinate rapid fixes and postmortems as needed
Change Management: Champion the adoption of AI tools within customer-facing teams, supporting the development of training materials and enablement sessions dedicated to developing AI proficiency within CX

What we offer

Receive a competitive reward package – reevaluated each year – that includes salary, benefits, and pre-IPO equity
Enjoy 28 days of paid vacation, plus an additional day after 2 and 4 years
Make an impact on the environment and society with 1 (fully paid) Impact Day
Receive generous family leave, child support, mental health support, and sabbatical opportunities
We enjoy gathering for meals, cultural initiatives, and events like local Summer Sessions and year-end celebrations. There's also healthy snacks, drinks, and a weekly catered lunch
20 Flex Days per year to work remotely from other locations

Fulltime

Gen AI Solution Developer

The Markets Intelligence team focuses on developing commercial insights from int...

Location

United Kingdom , London

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Advanced expertise in machine learning, deep learning, and artificial intelligence, with a proven track record of developing complex AI-driven solutions
Strong proficiency in Python, preferred experience in web frameworks like FastAPI or Flask
Proven experience building or designing chatbots (a portfolio or links to examples are highly encouraged)
Demonstrated ability to effectively communicate and collaborate with technical and non-technical stakeholders (e.g., Sales, Trading, MQA)
Markets experience highly preferred
Deep familiarity with prompt engineering, context window optimization, and evaluation frameworks
Good understanding of agentic architectures, including planning, reasoning, and multi-agent collaboration, preferred knowledge in LangChain, LangGraph etc.
Experience integrating chatbots or AI systems into CRM systems, websites, or mobile applications
Knowledge of AI/ML pipelines or data labeling processes
Experience in Data Analytics and its distribution via Chatbots.

Job Responsibility

Collaborate cross-functionally with diverse teams including Sales, Trading, Market Quantitative Analysis (MQA), and Technology to design, develop, deploy, and manage the full lifecycle of Generative AI chatbot solutions
Design and implement chatbot flows, scripts, and user interactions across platforms (e.g., internal messaging apps)
Design, implement, and optimize Retrieval-Augmented Generation (RAG) pipelines using embedding models, vector databases, and context management techniques
Build and utilize agentic frameworks that enable multi-step reasoning, planning, and tool orchestration for end-to-end AI workflows
Integrate chatbots and AI pipelines with a variety of data sources, including structured (SQL, APIs, CRMs) and unstructured (text, PDFs) back-end systems
Use data analysis to create better models of human behavior and other complex systems
Stay current with the evolving Gen AI ecosystem, including AI/ML trends and best practices in conversational design and automation.

Fulltime

Product Design Intern, Conversation Intelligence

We seek driven designers to shape the future of AI Agent products at Cresta. Whe...

Location

Canada , Toronto

Salary:

30.00 - 50.00 USD / Hour

Cresta

Expiration Date

Until further notice

Requirements

Bachelor's degree or equivalent in UX Design, HCI, or a related field
Experience with designing AI Agents, Virtual Agents, or Conversational AI
Strong portfolio showcasing user-centric design thinking, polished UI craftsmanship, and innovative interaction paradigms
Excellence in prototyping: skilled at using tools like Cursor, Claude Code, V0, or the latest AI tools to build realistic prototypes
Proficiency in design tools such as Figma, prototyping tools such as Cursor, Claude or V0 to create interactive prototypes
Strong at product thinking + a blend of UX disciplines (interaction design, prototyping, visual design, and user research)
Have a deep curiosity about the underlying tech of our products

Job Responsibility

Generate novel UX ideas for AI Agents, considering the needs of various user personas
Think through user and business problems, propose reasonable solutions, create detailed mockups, prototype to explore further and work with engineers to build them
Actively involved in defining product strategy and feature requirements
Constantly talk to our customers from contact centers - gathering insights into user pain points before and during the development process, and validating features to improve usability
Collaborate closely with Engineers, PMs, ML experts, Customer Success, and Sales
Be the design advocate and push for the highest quality of the polish
Constantly identify areas of opportunities and future work for the products
Have good judgment of when to ship: perfect is the enemy of good

What we offer

Lunch can be expensed (up to $25) while working in the office
PT0: 4 days
Compensation for this position includes a base salary, equity, and a variety of benefits

New

Staff Software Engineer

This position will design and build intelligent AI agent systems, LLM-based appl...

Location

United States , Dallas

Salary:

Not provided

JLL

Expiration Date

Until further notice

Requirements

4-6 years’ hands-on experience working as Sr AI/ML Developer with at least three complete agentic AI system implementations
4-6 years’ hands-on experience with cloud AI services (Azure OpenAI, AWS Bedrock, Google Vertex AI)
4-6 years hands-on experience with Python AI/ML frameworks (LangChain, LlamaIndex, Transformers, PyTorch)
4-6 years’ hands-on experience integrating LLMs with external systems and enterprise applications
Experience working with vector databases, knowledge graphs, and RAG pipeline development
Advising on best practices for AI agent development and enterprise AI integration processes
Experience in deploying AI models and agents in multiple environments (dev, staging, production)
Experience managing stakeholder communication regarding AI capabilities, limitations, and project timelines, including managing expectations, foreseeing AI-related risks and reporting them
Proficient in developing, deploying, and orchestrating multi-agent AI systems
Demonstrated proficiency in LLM fine-tuning, prompt engineering, and model optimization

Job Responsibility

Design and build intelligent AI agent systems, LLM-based applications, and autonomous workflow solutions within the context of our enterprise applications
Provide expertise in Large Language Models, multi-agent architectures, RAG systems, Python development, cloud AI services, and enterprise AI integration
Develop and deploy agentic AI solutions that can autonomously perform complex business tasks

What we offer

401(k) plan with matching company contributions
Comprehensive Medical, Dental & Vision Care
Paid parental leave at 100% of salary
Paid Time Off and Company Holidays
Early access to earned wages through Daily Pay

Fulltime

New

GenAI Engineering Lead

We are seeking an exceptional and highly motivated GenAI Tech Lead to join our d...

Location

India , Pune

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

10-15 years of relevant experience in Apps Development or systems analysis role, with a significant portion dedicated to AI/ML and demonstrable hands-on experience in designing, building, and deploying real-world Generative AI solutions, with a specific focus on GenAI adoption and Agentic AI for business process automation
Proficiency in at least two programming languages. Strong preference for Python, with significant experience in Javascript/Typescript and Golang being highly valued
Demonstrated deep hands-on experience in engineering and deploying enterprise-grade solutions that are highly scalable, resilient, and performant
Strong theoretical and practical understanding of Large Language Models (LLMs), including experience with various open-source and proprietary models, fine-tuning techniques, and deployment strategies
Proficiency with transformers, agentic frameworks, vector stores, and advanced search algorithms
Hands-on experience with Retrieval Augmented Generation (RAG) implementations
Experience with relevant GenAI/ML frameworks such as LangChain, LangGraph, MLFlow, Spring AI, Spring Boot, and Flask
Extensive experience with data analysis and manipulation using tools like SQL and Pandas
Proficiency in database technologies including Oracle, Postgres, or MongoDB
Proven experience in designing and implementing robust REST and WebSocket APIs

Job Responsibility

Strategic Leadership & GenAI Adoption: Drive the identification, evaluation, and adoption of emerging Generative AI technologies and tools to develop innovative solutions and enhance existing platforms. Actively design, develop, and implement AI/ML solutions within financial applications, with a strong emphasis on practical GenAI adoption. This includes hands-on coding, prototyping, and deploying GenAI solutions
Agentic AI for Business Process Automation: Lead the end-to-end design, prototyping, and implementation of Agentic AI solutions focused on automating critical business processes, ensuring they address business needs and scale effectively across the enterprise. This includes designing and implementing Retrieval Augmented Generation (RAG) systems to enhance accuracy and contextuality, especially for financial data
Chatbot Development: Design, develop, and deploy intelligent chatbot solutions capable of interacting with users across both structured data sources and unstructured data, leveraging GenAI for natural language understanding and generation in complex conversational flows
Document Processing & OCR Integration: Implement solutions for processing and extracting information from documents, including integrating Optical Character Recognition (OCR) technologies to handle scanned documents and images, making their content available for GenAI models
Text-to-SQL Implementation: Develop and deploy solutions leveraging Large Language Models to facilitate Text-to-SQL capabilities, enabling users to generate SQL queries from natural language requests, thus simplifying data access and analysis from structured databases
Data Analysis & Feature Engineering: Analyze large, complex datasets, identify intricate patterns, and extract actionable insights, leveraging GenAI capabilities for data augmentation or synthetic data generation, particularly relevant for Agentic AI applications
Data Pipeline Development: Build and maintain robust, scalable data pipelines for data ingestion, processing, and transformation, specifically optimizing for the unique requirements of GenAI model training and inference
Cross-Functional Collaboration: Partner with multiple management teams and business stakeholders to deeply understand requirements and translate them into precise technical specifications and actionable roadmaps, incorporating GenAI and Agentic AI possibilities into discussions
System Enhancements & Architecture: Identify and define necessary system enhancements to deploy new GenAI products and process improvements. Ensure application design adheres to the overall architecture blueprint, integrating GenAI and Agentic AI components seamlessly
Problem Resolution: Resolve a variety of high-impact problems/projects through in-depth evaluation of complex business processes, system processes, and industry standards, applying GenAI and Agentic AI where they can offer innovative solutions

Fulltime

Staff AI Engineer

As a Staff AI Engineer on our AI Engineering team, you will be responsible for b...

Location

United States

Salary:

200000.00 - 280000.00 USD / Year

Apollo.io

Expiration Date

Until further notice

Requirements

8+ years of software engineering experience with a focus on production systems
1.5+ years of hands-on LLM experience (2023-present) building real applications with GPT, Claude, Llama, or other modern LLMs
Demonstrated experience building customer-facing, scalable LLM-powered products with real user usage
Experience building multi-step AI agents, LLM chaining, and complex workflow automation
Deep understanding of prompting strategies, few-shot learning, chain-of-thought reasoning, and prompt optimization techniques
Expert-level Python skills for production AI systems
Strong experience building scalable backend systems, APIs, and distributed architectures
Experience with LangChain, LlamaIndex, or other LLM application frameworks
Proven ability to integrate multiple APIs and services to create advanced AI capabilities
Experience deploying and managing AI models in cloud environments (AWS, GCP, Azure)

Job Responsibility

Design and Deploy Production LLM Systems
Create sophisticated AI agents that can chain multiple LLM calls, integrate with external APIs, and maintain state across complex workflows
Develop and optimize prompting strategies
Build robust APIs and integrate AI capabilities with existing Apollo infrastructure and external services
Implement comprehensive evaluation frameworks, A/B testing, and monitoring systems
Optimize for cost, latency, and scalability across different LLM providers and deployment scenarios
Work closely with product teams, backend engineers, and stakeholders to translate business requirements into technical AI solutions
Build sophisticated multi-agent systems that can reason, plan, and execute complex sales workflows
Develop systems that maintain conversational context across complex multi-turn interactions
Build scalable large language model and agentic platforms

What we offer

equity
company bonus or sales commissions/bonuses
401(k) plan
at least 10 paid holidays per year, flex PTO, and parental leave
employee assistance program and wellbeing benefits
global travel coverage
life/AD&D/STD/LTD insurance
FSA/HSA and medical, dental, and vision benefits

Fulltime

Conversational AI Agents Developer

Sybrant Technologies

Location:

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
February 20, 2026

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