AI Specialist

2 weeks ago

Tirupati, India beBeeArtificialIntelligence Full time

We're looking for a highly skilled AI specialist to join our team.About the RoleThe successful candidate will be responsible for designing, building, and iterating large language model (LLM) powered workflows. This includes retrieval, routing, tool use, function calling, and multi-step agents.Additionally, they will implement agentic apps that plan, call tools/APIs, and maintain state across tasks. They will also build RAG pipelines: data ingestion, chunking, embeddings, indexing, and latency-optimized retrieval.The ideal candidate will own prompt engineering & evaluation (A/B tests, guardrails, metrics like latency, cost, quality, safety). They will productionize models/workflows with observability (traces, tokens, failures), cost controls, and fallbacks.They will ship backend services and APIs (e.g., Python/FastAPI) integrating with data stores and vector DBs.RequirementsThe following skills and qualifications are required:Hands-on experience with LLMs (OpenAI, Claude, Llama, etc.) and orchestration frameworks (LangChain, LlamaIndex, or custom).Proficiency in Python; building RESTful services, writing clean, tested code.Experience with RAG, vector databases (Pinecone, Weaviate, FAISS, Qdrant), embeddings.Understanding of agent patterns (tool calling, planning/execution, memory) and workflow engines.Familiarity with prompt design, safety/guardrails, and evaluation frameworks.Basics of cloud & deployment (AWS/GCP/Azure), Docker, Git, CI/CD.A strong debugging mindset and bias to ship.Bonus PointsThe following skills and qualifications are highly desirable:FastAPI/Flask, Celery/queues; streaming UIs.Model fine-tuning/LoRA, dataset curation, prompt-cache strategies.Monitoring/tracing (LangSmith, Weights & Biases, OpenTelemetry).Frontend basics (React/Next.js) to collaborate on UX.Data privacy, PII redaction, and security best practices.What You'll AchieveYou will reduce latency/cost per request, improve answer quality scores, increase workflow reliability (timeouts, retries, fallbacks) and on-call readiness, and speed up iteration from spec → prototype → production.

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