3 months ago
Base Salary
$72k - $97k/yr
Responsibilities
- Build GenAI applications using LLMs, RAG, agents, and tool-calling workflows.
- Develop multi-agent solutions with frameworks such as LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and LlamaIndex.
- Design workflows involving planners, retrievers, executors, validators, and human-in-the-loop agents.
- Build backend APIs and microservices using Python, FastAPI, and Flask.
- Integrate AI agents with enterprise systems, databases, APIs, document repositories, and cloud services.
- Implement document ingestion, embeddings, vector search, reranking, and retrieval pipelines.
- Deploy and monitor GenAI applications using Docker, Kubernetes, and cloud platforms.
- Support LLMOps through prompt and version management, model evaluation, monitoring, logging, and cost tracking.
Requirements
- Strong hands-on Python development experience.
- Experience with at least one of OpenAI, Azure OpenAI, AWS Bedrock, Anthropic Claude, Gemini, Llama, or Mistral.
- Hands-on experience with at least one agentic framework, including LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, or LlamaIndex.
- Understanding of RAG, embeddings, vector databases, semantic search, and prompt engineering.
- Experience with vector stores such as OpenSearch, Pinecone, FAISS, Chroma, Weaviate, Milvus, Azure AI Search, or pgvector.
- Knowledge of REST APIs, cloud deployment, Docker, CI/CD, and software engineering practices.
- Ability to work with structured and unstructured data, including documents, APIs, databases, and knowledge bases.
- Preferred experience with multi-agent orchestration, tool calling, memory, planning, reflection, and evaluation.
- Preferred exposure to MCP, Graph RAG, Neo4j, knowledge graphs, or entity extraction.
- Preferred knowledge of LangSmith, MLflow, Phoenix, Ragas, TruLens, Arize, or OpenTelemetry.
- Preferred experience with AWS Bedrock or SageMaker, Azure OpenAI or AI Search, or GCP Vertex AI.
- Understanding of AI guardrails, prompt-injection prevention, PII masking, access control, and responsible AI.
- Ability to explain at least one end-to-end GenAI or agentic AI project, including its problem, architecture, tools, deployment, evaluation, and business impact.
Benefits
- Comprehensive benefits package for regular, full-time employees, including paid time off, company holidays, personal days, and sick leave.
- Medical, dental, and vision coverage, or provincial healthcare coordination in Canada.
- Retirement savings plans such as 401(k) in the U.S. and RRSP in Canada.
- Life and disability insurance and employee assistance programs.
- Additional benefits may be available according to local policy and eligibility.
Tech Stack
Categories
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.