GenAI / Agentic AI Developer

GenAI / Agentic AI Developer

We are seeking a highly skilled and hands-on GenAI / Agentic AI Developer to design, build, and deploy enterprise-grade AI solutions powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent architectures.

The ideal candidate will have strong Python development expertise and practical experience implementing GenAI applications, agent orchestration frameworks, vector search technologies, and cloud-native AI solutions. This role requires someone who can move from proof-of-concept to production while ensuring scalability, reliability, security, and business value.

Key Responsibilities

• Design and develop GenAI solutions using LLMs, RAG, tool calling, and agent-based architectures.

• Build and orchestrate multi-agent workflows, including planner, retriever, executor, validator, and human-in-the-loop patterns.

• Develop backend services and APIs using Python, FastAPI, Flask, REST APIs, and microservices.

• Design and implement document ingestion, embedding generation, vector indexing, reranking, and retrieval pipelines.

• Integrate AI applications with enterprise systems, APIs, databases, document repositories, and cloud services.

• Deploy, monitor, and support GenAI applications using Docker, Kubernetes, CI/CD pipelines, and cloud platforms.

• Implement LLMOps best practices, including model evaluation, prompt management, monitoring, logging, observability, and cost optimization.

• Collaborate with business and technology stakeholders to deliver scalable AI solutions that generate measurable business outcomes.

• Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent professional experience.

• 5+ years of hands-on Python development experience.

• Experience building and deploying GenAI or Agentic AI applications in enterprise environments.

• Hands-on experience with one or more of the following:

• LangGraph

• LangChain

• AutoGen

• CrewAI

• Semantic Kernel

• LlamaIndex

• Strong understanding of:

• Retrieval-Augmented Generation (RAG)

• Embeddings

• Prompt Engineering

• Semantic Search

• Vector Databases

• Experience working with one or more of the following:

• OpenAI

• Azure OpenAI

• AWS Bedrock

• Anthropic Claude

• Gemini

• Llama

• Mistral

• Experience with vector platforms such as:

• OpenSearch

• Pinecone

• Chroma

• FAISS

• Weaviate

• Milvus

• Azure AI Search

• pgvector

• Experience developing REST APIs and cloud-native applications.

• Knowledge of Docker, Kubernetes, CI/CD, and software engineering best practices.

• Experience working with structured and unstructured data sources, including documents, PDFs, APIs, databases, and knowledge repositories.

• Preferred Qualifications

• Experience designing and deploying multi-agent AI systems.

• Experience with tool calling, memory management, autonomous planning, reflection, and evaluation techniques.

• Exposure to:

• MCP (Model Context Protocol)

• GraphRAG

• Neo4j

• Knowledge Graphs

• Entity Extraction

• Experience with LLMOps tools such as:

• LangSmith

• MLflow

• Phoenix

• Ragas

• TruLens

• Arize

• OpenTelemetry

• Experience with:

• Azure AI Foundry

• Azure OpenAI

• Azure AI Search

• AWS Bedrock

• AWS SageMaker

• GCP Vertex AI

• Knowledge of AI governance, responsible AI, AI guardrails, prompt injection prevention, PII masking, and access controls.

• Required Candidate Experience

Candidates must be able to clearly explain at least one end-to-end GenAI or Agentic AI implementation, including:

• Business problem being solved

• Overall solution architecture

• LLMs and frameworks leveraged

• Agent orchestration approach

• RAG and vector search design

• Deployment strategy

• Evaluation and monitoring methodology

• Business impact and measurable outcomes

• For this role, the gross annual starting base salary is 100,000–150,000 (full-time). This covers base pay only; any bonuses, incentives, and benefits will be discussed later in the recruitment process. Candidates with additional experience or qualifications may receive a higher offer, determined by objective, gender-neutral criteria and consistent with our pay principles. If a collective labour agreement applies, we will explain the relevant pay terms at the interview stage. Note: We never ask for your current or previous salary during our hiring process.

Ref. code:

• 506367

Posted on:

• Oct 3, 2026

Experience Level:

• Experienced Professionals

Contract Type:

• Permanent

Location

New York, US

Brand: Capgemini

Professional Community: Data & AI

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