Applied AI Engineer, Enterprise GenAI Job at Scale (San Francisco)

Staff Applied AI Engineer, Enterprise GenAI

The SGP ML team works on the front lines of this AI revolution. We interface dir...

Location

United States , San Francisco, CA; Seattle, WA; New York, NY

Salary:

216000.00 - 270000.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

7+ years of full-time engineering experience, post-graduation
A love for solving deeply complex technical problems with ambiguity using state of the art research and AI to accomplish your client's business goals
Strong engineering background: a Bachelor's degree in Computer Science, Mathematics, or another quantitative field or equivalent strong engineering background
Deep familiarity with a data-driven approach when iterating on machine learning models and how changes in datasets can influence model results
Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
Proficiency in Python to write, test and debug code using common libraries (ie numpy, pandas)

Job Responsibility

Own, plan, and optimize the AI behind our Enterprise customer's deepest technical problems
Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
Have experience gathering business requirements and translating them into technical solutions
Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
Push production code in multiple development environments, writing and debugging code directly in both our customer's and Scale's codebases
Be able and willing to multi-task and learn new technologies quickly

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
commuter stipend

Fulltime

Principal Engineer – GenAI & Applied AI

We are seeking a hands-on GenAI engineering leader to design and deliver agentic...

Location

India , Pune

Salary:

Not provided

Codvo AI

Expiration Date

Until further notice

Requirements

8+ years in software/AI engineering, with 3+ in LLMs/GenAI
Deep expertise in Python, orchestration frameworks, vector search
Strong exposure to cloud AI services (AWS Bedrock, Azure AI Foundry, GCP Vertex AI)
Track record of shipping production-grade AI systems

Job Responsibility

Architect agentic workflows, RAG systems, conversational AI solutions
Build accelerators and reusable components on frameworks like LangChain, LangGraph, Haystack
Integrate LLMs with vector databases, APIs, enterprise data sources
Implement AI evaluation, prompt optimization, safety guardrails
Mentor engineers, review code, set AI development best practices

Fulltime

Applied AI Engineer - MCP

We are hiring a founding group of engineers to kickstart this mission. As an AI ...

Location

India , Chennai

Salary:

Not provided

Appian Corporation

Expiration Date

Until further notice

Requirements

AI Infrastructure Experience: Professional experience building and deploying production-grade GenAI systems on GCP Vertex AI or AWS Bedrock including LLM APIs, agent frameworks, and RAG pipelines
Python Mastery: Deep proficiency in Python and common AI/ML libraries (e.g., LangChain, LlamaIndex, OpenAI SDK, Google Cloud AI SDK)
Agentic Systems: Hands-on experience building multi-step, tool-calling AI agents that operate reliably in production including tool schema design, structured outputs, and failure handling
MCP or Tool Protocol Experience: Familiarity with Model Context Protocol (MCP) or equivalent patterns for exposing enterprise resources to AI systems as callable, permissioned tools
Vector & Retrieval Systems: Experience with vector databases (Pinecone, pgvector, or similar) and embedding-based retrieval at scale
Technical Foundation: B.S. in Computer Science, Engineering, or a related technical field
The Pioneer Mindset: A self-starter who is excited to be part of a "first-of-its-kind" team and thrives in environments where you are building the playbook

Job Responsibility

Build the AI Platform: Design, deploy, and scale GenAI infrastructure on GCP Vertex AI (preferred) or AWS Bedrock
Build & Operate MCP Servers: Develop and maintain Model Context Protocol (MCP) servers that expose enterprise systems (databases, APIs, internal tools) as structured, AI-consumable capabilities
Design the Tool Layer: Build the tool registry and invocation framework that allows agents to interact with internal systems safely and reliably including schema design, access controls, and error handling
Engineer Agent-to-Agent Infrastructure: Architect the communication and coordination layer that allows specialized agents to delegate tasks, share context, and compose into larger autonomous workflows
Own the Retrieval Layer: Architect and operate RAG systems, including vector stores, embedding pipelines, chunking strategies, and retrieval evaluation frameworks
Establish AI Reliability: Instrument AI systems with logging, tracing, latency monitoring, and evaluation hooks so agents can be trusted, debugged, and improved in production

What we offer

health coverage
Employee Assistance Program (EAP) with free mental health support
life and disability insurance
Employee Stock Purchase Program (ESPP)
retirement/pension plan
wellness dollars
tuition reimbursement
family-forming benefits

Fulltime

Senior Applied AI Engineer

Microsoft is seeking a Senior Applied AI Engineer to join a pioneering team focu...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science, Engineering, Data Science, Math, Business, or related field AND 4+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
8+ years of professional software development experience with at least one of the following: C#, C++, or Java
8+ years of professional experience building cloud applications, preferably full stack
3+ years of experience with GenAI, LLMs, or agentic systems
Experience designing and implementing enterprise-scale services
Experience delivering Dynamics 365 and/or Power Platform solutions is desirable
Experience in agentic AI development and leveraging AI tools for development
Verbal, written, and cross-team collaboration skills

Job Responsibility

Design, build, and ship AI-powered software systems leveraging generative AI, LLMs, and agentic reasoning frameworks
Develop and integrate autonomous AI agents capable of task decomposition, multi-step planning, memory, tool usage, and dynamic decision-making across enterprise workflows
Apply state-of-the-art techniques including foundation models, prompt engineering, retrieval-augmented generation (RAG), multi-agent architectures, and classical machine learning where appropriate
Fine-tune and adapt foundation models using domain-specific data, and evaluate model behavior across relevance, quality, hallucination, bias, latency, and cost
Build rapid prototypes and translate them into production-grade systems, contributing to deployment, debugging, monitoring, and operational excellence
Design and implement evaluation frameworks and automated evaluators, using offline experiments, shadow testing, online experimentation, and telemetry to measure impact and guide iteration
Partner closely with product managers, researchers, and engineers to bring agentic capabilities into Microsoft’s business and productivity platforms
Write high-quality, well-documented, and maintainable code, along with clear technical design specifications
Mentor engineers and contribute to raising the overall engineering and applied AI bar across the team
Apply Responsible AI principles throughout the development lifecycle, proactively identifying and mitigating risks related to fairness, bias, privacy, security, and misuse

Fulltime

Director, Applied AI Engineering- Enterprise

Join the team shaping the future of AI at Scale. The Applied AI team works on th...

Location

United States , San Francisco; New York

Salary:

285200.00 - 356500.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

8+ years of experience building, deploying, and scaling ML systems in production, including Enterprise-grade Gen AI and agentic applications
6+ years of people leadership experience, including managing managers and leading multi-team organizations delivering customer-facing AI products
Deep applied expertise in Gen AI, including LLM-based systems, agent orchestration, evaluation and reliability frameworks, and production system design
Experience owning end-to-end AI product delivery—from problem definition and technical architecture to deployment, iteration, and scaling
Strong technical judgment across software engineering, system design, and applied ML fundamentals
Exceptional communication and stakeholder management skills, with the ability to influence executives, customers, and cross-functional partners
Bachelor’s degree required
Master’s or PhD in Computer Science or a related field strongly preferred

Job Responsibility

Drive enterprise impact with GenAI: Partner directly with customers to identify high-leverage opportunities for generative AI, design solutions, and deliver production systems that create clear business value
Lead and scale a GenAI-native Applied AI organization: Build, mentor, and manage multiple teams of Applied AI Engineers and ML Engineers who are native to modern GenAI technologies, agentic systems, and multimodal models
Set technical and strategic direction: Define best practices for agent development, evaluation, deployment, and iteration across customer engagements and internal product efforts
Bridge frontier research to real-world applications: Translate advances in LLMs, multimodal models, and agentic workflows into practical, scalable solutions across industries
Discover model limitations and inspire innovation: Identify failure modes, inefficiencies, and gaps in current models
use these insights to influence internal research, product roadmaps, and customer strategy
Partner cross-functionally: Work closely with Product, Research, Sales, and Leadership to shape Applied AI offerings, prioritize investments, and guide long-term platform evolution
Influence the broader AI ecosystem: Represent Scale’s Applied AI capabilities with customers and partners, and help position Scale as a trusted leader in enterprise GenAI deployment

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO
equity based compensation
commuter stipend

Fulltime

Senior Data Scientist – Gen AI Engineer - Assistant Vice President

Location

India , Pune

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related quantitative field.
8–12 years of experience as a Data Scientist or equivalent role, with at least 2 years of specialized, hands-on experience in Generative AI, including leading technical development and mentoring teams.
Demonstrable experience across the full lifecycle of production-level GenAI projects — from ideation and prototyping through deployment, monitoring, and ongoing maintenance in live environments.
Expert-level Python proficiency
Scikit-learn, XGBoost, LightGBM
PyTorch
Hugging Face Transformers, LangChain, LlamaIndex, Semantic Kernel
LangGraph, CrewAI, AutoGen
Transformer architectures
RAG patterns

Job Responsibility

Working with financial and enterprise data, applying modern NLP and GenAI techniques to solve business problems.
Designing, refining, and systematizing prompt engineering strategies for large language models (LLMs), including structured prompting, chain-of-thought, and few-shot/zero-shot approaches.
Collaborating with business stakeholders to translate requirements into GenAI-powered solutions.
Developing, testing, and maintaining production-grade Python code for GenAI applications.
Integrating with vector databases (e.g., Pinecone, Weaviate, Milvus, pgvector, Qdrant) for retrieval-augmented generation (RAG) pipelines.
Building, monitoring, and optimizing MLOps/LLMOps pipelines for continuous model deployment and observability.
Researching and evaluating emerging GenAI technologies, frameworks, and best practices to maintain competitive advantage.
Troubleshooting and debugging GenAI models and agentic systems in production, including rapid identification and resolution of issues in real-world deployments.
Communicating complex AI/ML concepts clearly to non-technical stakeholders, translating technical jargon into actionable business terms.
Participating in and leading team meetings, design reviews, and architecture discussions.

Fulltime

Azure Data Science Platform Engineer (AI)

WFH flexibility! Up to 4 days/week! Global Environment! Competitive salary! We a...

Location

Japan , Tokyo 23 wards

Salary:

7000000.00 - 12000000.00 JPY / Year

Randstad

Expiration Date

February 29, 2028

Requirements

Bilingual proficiency in Japanese and English is preferred (English is a MUST)
Day-to-day communication will primarily be in English, with occasional interaction with Japanese-speaking stakeholders
6+ years of experience in data science, machine learning, advanced analytics, or applied AI, with demonstrated business results
Strong experience taking solutions from development into production and supporting them in live environments
Strong Python programming skills and solid engineering discipline
Experience with GenAI / LLM use cases or solution delivery
Hands-on experience with Azure for deploying, supporting, or operating production workloads
Strong experience with Terraform and Infrastructure as Code in enterprise cloud environments
Experience with CI/CD, GitHub Actions, deployment automation, and DevOps practices
Experience with SRE, MLOps, or LLMOps, particularly in monitoring, incident handling, reliability, and operational support

Job Responsibility

We are looking for a candidate who combines strong data science delivery capability with practical production and operational ownership
This is not a pure research role and not a pure platform role. It is intended for someone who can build business-facing AI/ML solutions and also help ensure those solutions are deployable, stable, and maintainable
The ideal candidate is proactive, technically hands-on, comfortable working independently, and effective in cross-functional enterprise environments.

What we offer

WFH flexibility! Up to 4 days/week!
Global Environment!
Competitive salary!
健康保険
厚生年金保険
雇用保険
土曜日
日曜日
祝日

Fulltime

AI Engineer

We're hiring an AI Engineer to design and deliver production-grade GenAI and Age...

Location

Spain , Barcelona

Salary:

Not provided

FSP

Expiration Date

Until further notice

Requirements

2+ years’ experience in AI engineering, software development or data science, with a strong recent focus on GenAI and LLMs
Hands-on experience with GenAI orchestration frameworks and cloud platforms, including Azure AI Foundry, CrewAI, LangChain, Semantic Kernel, Hugging Face and Azure ML Studio
Strong capability in prompt and context engineering, RAG pipeline design, and LLMOps, including tooling such as PromptFlow, LangSmith, prompt versioning and LLM cost management
Experience working with Azure data and analytics services, including Data Factory, Data Lake, Synapse Analytics and Azure SQL Database
Strong programming skills (Python, C# or similar), with experience using Azure DevOps/GitHub CI/CD, and working across the software development lifecycle, including access control, audit logging, documentation, knowledge transfer and training

Job Responsibility

Deploy, fine-tune and monitor Generative AI models and Agentic AI systems for enterprise use cases
Develop and implement Retrieval-Augmented Generation (RAG) pipelines and advanced prompt and context engineering strategies
Design and implement multi-agent systems using orchestration frameworks such as CrewAI, Semantic Kernel or LangGraph
Integrate Agentic AI into business workflows and collaborate with data engineers to bring agentic capabilities to production
Implement LLM evaluation pipelines to assess output quality, accuracy and safety
Apply responsible AI principles including fairness, transparency and auditability, particularly for regulated public sector environments
Apply AI safety, guardrails and output validation controls to ensure robust, compliant production deployments
Evaluate and recommend emerging GenAI tools and agentic frameworks for client applicability, driving innovation within the team

What we offer

Collaborative and supportive environment in which you can grow and develop your career
The tools and opportunity to do work you can be proud of
A chance to work alongside some of the best people in the industry, who always seek to share their knowledge and experience
Hybrid working
Industry leading coaching and mentoring
Competitive salary and an excellent benefits package

Fulltime

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Applied AI Engineer, Enterprise GenAI

Job Description

Job Responsibility

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