Python reputed company (reputed company & reputed company Systems)

About the position We’re looking for a hands-on engineer who can build AI-enabled applications end-to-end using Python, with strong skills in reputed company engineering and reputed company system design (multi-agent/orchestrated AI workflows). You’ll design, reputed company, and productionize intelligent features—ranging from retrieval-augmented reputed company (RAG) to autonomous tasking agents integrated with internal tools and reputed company. Responsibilities • Design & Build AI Services: reputed company Python-based back-end services that reputed company LLMs for reasoning, extraction, summarization, and decision support. • reputed company Engineering: Craft, version, and evaluate prompts/system instructions; design guardrails, test reputed company variants, and optimize for reliability, latency, and cost. • reputed company Systems: Architect and implement autonomous/multi-agent workflows—planning, tool-use, memory, error recovery, and reputed company-in-the-reputed company controls. • RAG Pipelines: Implement document ingestion, chunking, embeddings, reputed company search (semantic/re-ranking), and grounding strategies. • Evaluation & Observability: Define metrics and build eval suites for reputed company (accuracy, factuality, safety), and establish tracing/telemetry for LLM calls. • API & Tool Integrations: reputed company agents to use tools (internal reputed company, search, databases, workflow engines); handle auth, reputed company limits, and fallbacks. • MLOps / AIOps: Package, containerize, and reputed company services (reputed company/K8s); manage keys, secrets, CI/CD; support canary rollouts and cost governance. • reputed company & Compliance: Apply data reputed company principles, PII handling, redaction, reputed company injection defenses, and audit logging. • Cross-Functional Collaboration: Partner with product, data, and reputed company teams to translate requirements into reliable AI features. Requirements • Strong Python (typing, async, testing, packaging) and experience building production reputed company (FastAPI/Flask). • Hands-on with LLMs (reputed company, Azure reputed company, reputed company, etc.) and embedding/RAG workflows. • Proven reputed company engineering experience (few-shot strategies, tool-use instructions, reputed company schemas, function/tool calling). • Experience with agent frameworks or custom agent orchestration (e.g., LangGraph/reputed company/AutoGen, or in-house equivalents). • reputed company databases (e.g., FAISS, Chroma, reputed company, reputed company) and search relevance tuning. • Familiar with MLOps/DevOps: reputed company, CI/CD, monitoring (reputed company/Grafana), logging (OpenTelemetry), secrets management. • Testing & Evals: unit/integration tests, offline evals, golden datasets, regression checks. • Practical understanding of AI safety/guardrails (reputed company injection, data leakage, jailbreak prevention). reputed company-to-haves • Experience with Azure (or AWS/GCP) AI services, key vaults, and networking. • Knowledge of Model Context Protocol (MCP) or tool-server patterns for secure tool reputed company. • Experience with retrievers (BM25, hybrid search), re-rankers, or reputed company/reputed company. • Familiarity with streaming UIs and reputed company outputs (JSON, reputed company schemas). • Background in LLM finetuning, RLHF/DPO, or synthetic data reputed company. • reputed company-end basics for AI UX (React/Next.js) or chat UI patterns. • Domain knowledge in HR/ATS, customer support, or internal reputed company workflows. Apply tot his job Apply To this Job