Tata Consultancy Services
AI/ML full stack developer
Tata Consultancy Services, San Jose, California, United States, 95199
Must Have Technical/Functional Skills:
5+ years building production web apps/services; 1-2+ years with LLMs/RAG/agents. Proven
end-to-end
ownership: shipped at least one LLM/Agent system to real users. Strong
Python
(3.10+),
FastAPI , async patterns;
TypeScript
with
React/Next.js . Solid
RAG
fundamentals (indexing, embeddings, hybrid search, re-ranking, evals) and
Agent
patterns (tooling, retries, timeouts, circuit breakers). Experience with
vector databases
(pgvector/Milvus/Weaviate) and
Postgres . CI/CD (GitHub Actions), Containers/K8s, IaC (Terraform), and cloud (AWS/Azure/GCP). Testing discipline: unit/integration/e2e, load tests, contract tests; strong debugging & profiling. Clear communication, product sense, and trade-off thinking (latency/cost/quality/safety). Roles & Responsibilities:
Convert research POCs into production-grade services with SLAs, on-call readiness, and guardrails. Design and ship agentic workflows (tool use, function calling, orchestration graphs, retries, fallbacks). Build robust RAG pipelines: ingestion chunking indexing retrieval re-ranking grounded generation. Implement evaluation & LLMOps: golden sets, regression tests, CI eval gates, telemetry dashboards, A/B and canarying. Develop React/Next.js frontends for multi-step agents, streaming outputs, uploads, and auth flows. Build and document FastAPI backends (async, OpenAPI, pagination, rate limits, idempotency, background jobs). Operate via Kubernetes with Docker images, IaC (Terraform), GitHub Actions, and S3/GCS/Azure Blob storage. Add observability (OpenTelemetry, logs/metrics/traces, cost & token spend) and performance/cost tuning. Partner with Product, Sec/Compliance, and Platform to meet privacy, audit, and governance needs. Establish coding standards, testing strategy, and incident/rollback playbooks. Salary Range: $68,000-$130,000 a year#LI-CM2
5+ years building production web apps/services; 1-2+ years with LLMs/RAG/agents. Proven
end-to-end
ownership: shipped at least one LLM/Agent system to real users. Strong
Python
(3.10+),
FastAPI , async patterns;
TypeScript
with
React/Next.js . Solid
RAG
fundamentals (indexing, embeddings, hybrid search, re-ranking, evals) and
Agent
patterns (tooling, retries, timeouts, circuit breakers). Experience with
vector databases
(pgvector/Milvus/Weaviate) and
Postgres . CI/CD (GitHub Actions), Containers/K8s, IaC (Terraform), and cloud (AWS/Azure/GCP). Testing discipline: unit/integration/e2e, load tests, contract tests; strong debugging & profiling. Clear communication, product sense, and trade-off thinking (latency/cost/quality/safety). Roles & Responsibilities:
Convert research POCs into production-grade services with SLAs, on-call readiness, and guardrails. Design and ship agentic workflows (tool use, function calling, orchestration graphs, retries, fallbacks). Build robust RAG pipelines: ingestion chunking indexing retrieval re-ranking grounded generation. Implement evaluation & LLMOps: golden sets, regression tests, CI eval gates, telemetry dashboards, A/B and canarying. Develop React/Next.js frontends for multi-step agents, streaming outputs, uploads, and auth flows. Build and document FastAPI backends (async, OpenAPI, pagination, rate limits, idempotency, background jobs). Operate via Kubernetes with Docker images, IaC (Terraform), GitHub Actions, and S3/GCS/Azure Blob storage. Add observability (OpenTelemetry, logs/metrics/traces, cost & token spend) and performance/cost tuning. Partner with Product, Sec/Compliance, and Platform to meet privacy, audit, and governance needs. Establish coding standards, testing strategy, and incident/rollback playbooks. Salary Range: $68,000-$130,000 a year#LI-CM2