Senior BE Software Engineer (MCP & AI Agents) Job at SNI sp. z o.o. (Prague)

Senior Software Engineer, AI Runtime

We’re seeking a Senior Software Engineer to help power the future of agentic AI ...

Location

United States

Salary:

157000.00 - 198900.00 USD / Year

Apollo GraphQL

Expiration Date

Until further notice

Requirements

Expertise in agent-to-tool orchestration, routing, and coordination in scalable, fault-tolerant systems
Deep expertise in Rust programming language
Strong background in distributed systems, server architecture, and high-performance backend development
Proven experience with protocol design, message routing, and server-side orchestration frameworks
Experience building and maintaining robust runtime infrastructure that supports AI-driven workflows and enables reliable agent-to-tool interactions
Proven experience with protocol design, message routing, and building server-side frameworks that enable scalable, reliable multi-tool agent workflows
Hands-on experience with observability, monitoring, and debugging frameworks for complex systems
Passion for clean, maintainable code, high system reliability, and scalable architecture
Experience in strategic system design, making architectural trade-offs, and planning for long-term scalability and maintainability
Strong technical leadership and mentorship, including guiding junior engineers and driving engineering best practices across teams

Job Responsibility

Scale an enterprise AI/MCP Server and Gateway that powers multi-agent workflows across Apollo, including routing, orchestration, and integration boundaries
Implement robust server infrastructure to ensure reliability, performance, and security at scale
Build and maintain tools for agent discovery, communication, and coordination
Define deployment strategies and runtime optimizations to maximize efficiency and minimize operational overhead
Develop frameworks and patterns that enable seamless multi-agent collaboration and AI-driven orchestration
Integrate observability, logging, and monitoring for full visibility into server and agent behavior
Explore and implement AI-enhanced developer workflows to optimize orchestration and agent interactions
Collaborate with teams within our org to ensure the MCP Server meets evolving product and developer needs

Senior Software Engineer, AI

As a Senior AI Engineer on our Core AI team, you will be a cornerstone of FloQas...

Location

India , Pune

Salary:

Not provided

FloQast

Expiration Date

Until further notice

Requirements

6+ years of professional software engineering experience
3+ years focused on building backend for production applications
Mastery of Python
Familiarity with some AI application frameworks, context engineering, and scalable system design for AI products
Expertise in designing products that integrate with multiple technologies, APIs, and data sources in cloud-native environments (AWS preferred)
Strong desire to develop deep hands-on experience with LLM APIs, retrieval-augmented generation (RAG), conversational AI, document processing, and MCP integrations
Proven ability to lead tech product initiatives, establish technical standards and communicate complex system designs to both technical and business stakeholders

Job Responsibility

Architect and lead development of production AI products including intelligent chatbots, document processing systems, and agentic workflows using Python and modern AI frameworks
Design and implement our centralized AI platform including model routing, provider management, vector search, and AI application frameworks with seamless MCP (Model Context Protocol) integrations
Build scalable AI products that integrate with diverse technologies including accounting systems, document repositories, and external APIs while maintaining robust monitoring and observability
Master context engineering and system design for AI applications, ensuring optimal information retrieval, context assembly, and multi-turn conversation management
Collaborate with Product, Engineering, and Security teams to ensure AI products are robust, compliant, and aligned with business objectives in the regulated accounting space
Provide technical leadership and mentorship to the growing AI team, establishing best practices for AI product development, deployment, and governance

Fulltime

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

Senior AI Engineer

HPE Galway are seeking a highly skilled Senior AI Engineer to join our growing A...

Location

Ireland , Galway

Salary:

Not provided

Hewlett Packard Enterprise

Expiration Date

Until further notice

Requirements

Bachelor’s degree in computer science, AI/ML or related technology
Minimum of 8+ years of work experience in cloud based and/or open source software development
3+ years of experience in AI/ML engineering with a focus on LLMs and knowledge retrieval systems
Strong hands-on experience with LLM frameworks: LangChain, LangGraph, PydanticAI, or similar
Proven experience implementing RAG systems and vector databases (PostgreSQL with pgvector, Pinecone, FAISS, Weaviate, Chroma)
Proficiency in Python with deep knowledge of ML libraries (PyTorch, TensorFlow, Transformers)
Experience with Model Context Protocol (MCP) server development and deployment
Understanding of Google ADK and A2A protocol implementations
Strong knowledge of cloud platforms (AWS, Azure, GCP) and their AI/ML services
Experience with prompt engineering, fine-tuning, and LLM optimization techniques

Job Responsibility

Design and develop AI-driven applications leveraging large language models (LLMs), retrieval-augmented generation (RAG), and Graph RAG architectures
Implement and optimize RAG techniques for improved knowledge retrieval and contextual reasoning
Build and maintain graph-based AI solutions using modern frameworks like LangGraph, PydanticAI, and LangChain
Develop and deploy Model Context Protocol (MCP) servers for seamless data integration across various sources
Design scalable vector database solutions using Pinecone, Weaviate, or similar technologies
Integrate Google Agent Development Kit (ADK) and Agent-to-Agent (A2A) protocols for multi-agent workflows
Collaborate with cross-functional teams to translate business requirements into technical AI solutions
Maintain high code quality standards and implement comprehensive testing strategies

What we offer

Health & Wellbeing
Personal & Professional Development
Unconditional Inclusion

Fulltime

Senior Machine Learning Engineer

Join Truveta’s Intelligence Platform and Applications team to engineer the next ...

Location

United States , Seattle

Salary:

165000.00 - 190000.00 USD / Year

Truveta

Expiration Date

Until further notice

Requirements

5+ years of experience building and deploying scalable, production-ready ML systems in a collaborative engineering environment
Proficiency with agentic AI frameworks (e.g., LangGraph, AutoGen, CrewAI) and understanding of interoperability protocols such as MCP and A2A
Hands-on experience fine-tuning and optimizing large language models (LLMs) or multimodal models, using techniques such as LoRA, PEFT, and TRL
Experience working with vector databases and embeddings, integrating FAISS, Pinecone, Chroma, or Azure AI Search into retrieval-augmented generation (RAG) or semantic-search pipelines
Strong software engineering fundamentals, with proficiency in Python and experience designing scalable systems in modern cloud environments (Azure, AWS, or GCP)
B.S. or M.S. in Computer Science, Artificial Intelligence, or a related technical field

Job Responsibility

Design and reason with agentic AI frameworks
Bring a deep understanding of LLM fundamentals
Work fluently with embeddings and vector stores
Excel at model fine-tuning
Think and build like engineers
Collaborate across boundaries
Demonstrate senior-level ownership
Understand evaluation deeply
Adapt and learn continuously
Act with purpose

What we offer

Interesting and meaningful work for every career stage
Great benefits package
Comprehensive benefits with strong medical, dental and vision insurance plans
401K plan
Professional development & training opportunities for continuous learning
Work/life autonomy via flexible work hours and flexible paid time off
Generous parental leave
Regular team activities (virtual and in-person)

Fulltime

Distinguished Engineer- AI Agentics Engineering

At CVS Health, we’re building a world of health around every consumer and surrou...

Location

United States , Woonsocket

Salary:

175100.00 - 334750.00 USD / Year

CVS Health

Expiration Date

March 31, 2026

Requirements

15+ years of Software Engineering experience required
7+ years in AI/ML engineering with 3+ years specifically in agentic AI or autonomous systems
Proven experience building multi-agent systems from scratch (not just fine-tuning existing models)
Deep expertise in: Multi-agent system architectures: Actor model frameworks, distributed consensus protocols, agent communication standards (FIPA-ACL, KQML, MCP, A2A), and coordination patterns (hierarchical, peer-to-peer, marketplace-based)
LLM Integration Platforms: OpenAI API, Anthropic Claude API, Azure OpenAI Service, Google Vertex AI, and on-premises LLM deployment (vLLM, TensorRT-LLM, Ollama)
Agentic Frameworks: LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and custom agent runtime environments
Tool-using AI Systems: Function calling implementations, API integration patterns, IDE (Cursor, Windsurf), Notebooks (Jupyter), tool selection algorithms, and sandbox execution environments for safe tool usage
Agent Orchestration Platforms: Kubernetes-based agent deployment, Apache Airflow for agent workflows, Temporal for durable agent executions, Agentspace, and event-driven architectures (Apache Kafka, RabbitMQ)
Vector Databases & Knowledge Systems: Pinecone, Weaviate, Chroma, Qdrant for agent memory systems, and knowledge graph technologies (Neo4j, Amazon Neptune, Apache Jena)
Real-time Inference Infrastructure: NVIDIA Triton Inference Server, Ray Serve, TorchServe, and streaming architectures for sub-100ms agent response times

Job Responsibility

Strategic Agentic Architecture & Design: Drive the end-to-end architecture for highly scalable, multi-agent systems that can operate autonomously across complex enterprise workflows
Partner with other Principal Engineers, AI Architects, and executive leadership to shape the long-term agentic roadmap
Champion best practices for agent reliability, interpretability, safety, and performance optimization
Agent Platform Development & Orchestration: Oversee the design and development of new AI agent platforms from the ground up
Implement robust agent lifecycle management, including spawning, monitoring, termination, and inter-agent communication protocols
Foster an engineering culture that values agent autonomy, emergent intelligence, and continuous learning capabilities
Multi-Agent Systems & Emerging AI Technologies: Provide thought leadership on how multi-agent systems, large language models, and reinforcement learning create unique demands on infrastructure
Understand how to move AI agents from proof-of-concept to production-ready autonomous systems
Evaluate and recommend emerging agentic technologies and guide their integration into the broader technology stack
Cross-Functional Leadership & AI Mentoring: Serve as a key technical advisor for C-level executives and product leaders

What we offer

Affordable medical plan options
401(k) plan (including matching company contributions)
Employee stock purchase plan
No-cost programs for all colleagues including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching
Paid time off
Flexible work schedules
Family leave
Dependent care resources
Colleague assistance programs
Tuition assistance

Fulltime

!

Senior AI Engineer

Guidepoint is seeking an experienced Senior AI Engineer to join our Toronto-base...

Location

Canada , Toronto

Salary:

Not provided

Modoras Accounting Syd

Expiration Date

Until further notice

Requirements

6+ years of professional experience (or 5+ with a Master’s degree) designing, building, and scaling distributed, production-grade backend systems
2+ years building and operating Generative AI and agentic systems in production
Strong software engineering fundamentals in Python, including building and scaling REST APIs using frameworks such as FastAPI, with experience in asynchronous programming and microservices
Hands-on experience building enterprise AI agents and workflows using LLM platforms such as OpenAI, Anthropic (Claude), or Google Gemini, and frameworks like LangChain or agent SDKs
Experience building and operating within the enterprise AI ecosystem, including custom GPTs or agents, agent builders, connectors/apps, and application or agent SDKs (e.g., OpenAI Apps SDK, ChatKit, or equivalents)
Experience designing and operating agent integration layers (e.g., MCP servers or similar) that connect AI agents to internal APIs, tools, and services, with secure authentication and authorization using enterprise identity platforms such as Okta, Microsoft Entra ID, or OAuth-based systems
Strong understanding of AI governance, compliance, and responsible AI practices, including access control, auditability, data handling, and secure deployment of AI systems in enterprise environments
Direct experience with RAG, vector search using databases such as Elasticsearch, multi-agent AI systems, tool-calling agents, prompt engineering, and agent evaluation in production environments
Cloud-native experience deploying and operating containerized applications on Azure (preferred) or AWS/GCP using Docker and Kubernetes
Proven ability to lead complex technical initiatives, make sound architectural decisions, and mentor engineers building production-ready AI systems

Job Responsibility

Design, build, and operate scalable, low-latency backend services and REST APIs that power Generative AI capabilities, including retrieval-augmented generation (RAG) pipelines, vector search, and enterprise-grade agentic systems
Own the full lifecycle of AI applications and agents, from system architecture and development to CI/CD, deployment, agent evaluation, monitoring, and ongoing optimization in production
Build production-grade research agents and enterprise AI workflows that integrate LLMs with proprietary knowledge, vector databases (e.g., Elasticsearch), internal tools, external APIs, and real-time data
Design and operate multi-agent AI systems, including tool-calling agents and agent orchestration patterns, to support complex research and enterprise workflows
Apply AIOps best practices for building, evaluating, deploying, and operating AI agents with strong observability, reliability, and quality controls
Continuously improve retrieval and generation quality using prompt engineering, retrieval tuning, re-ranking, advanced chunking strategies, and hallucination reduction techniques
Provide technical leadership through design discussions, code reviews, and mentorship, and partner closely with product and business stakeholders to influence the AI roadmap

What we offer

Paid Time Off
Comprehensive benefits plan
Company RRSP Match
Development opportunities through the LinkedIn Learning platform

Senior BE Software Engineer (MCP & AI Agents)

SNI sp. z o.o.

Location:
Czech Republic , Prague

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
February 08, 2026

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