Job Description
Job Description:
Role: Senior AI Engineer
Experience: 8+ Years
Notice period: Only Immediate to 15 days ( Who are serving notice period preferred)
Duration: 6 Months Contract
Location: Fully Remote (India)
Work Hours:
- March - November: 12:30 PM 9:30 PM IST
- NovemberMarch: 1:30 PM – 10:30 PM IST
Overview:
Deep expertise in LLM implementation, RAG architectures, prompt engineering, retrieval optimization, and semantic search
Experience processing unstructured content using OCR, chunking strategies, embeddings, reranking, and document intelligence workflows
Hands-on builder who has developed and deployed AI applications in production rather than purely research or data science environments
Key Responsibilities:
Conversational Agents: Implement LLM agents with tool/function calling, dialogue state, guardrails, and safety
RAG Pipelines: Build indexing, chunking, embeddings, reranking, and hybrid retrieval for high-precision answers
Document AI: Ingest and parse complex PDFs using OCR, multimodal LLM image understanding (sending full images to an LLM to describe, detect structure, and extract context), table extraction, and layout-aware parsing
Prompt Engineering: Design and iterate prompts, templates, few-shot examples; run A/B and automated evaluations
Evaluation & Operations: Measure grounding, hallucination, latency, and cost; deploy and monitor in cloud with observability
Project Documentation & Communication: Creating and maintaining the written project documentations including requirements, technical designs, test plans, runbooks, release notes, user guides, risk/issue logs, change records, status updates, meeting notes, incident/outage notices, and decision summaries
Skills
Business & Communication
- Demonstrated business analysis skills with 3+ years of experience leading customer/client facing workshops and discussions
Excellent written and verbal communication skills, with the ability to present complex ideas clearly to both technical and non-technical audiences - LLM / AI
- 3+ years building ML/AI applications, including 2+ years with LLMs + RAG
Practical understanding of AI and automation technologies, including RPA, generative AI, and intelligent automation platforms
Programming & Frameworks
Strong Python
Experience with LangChain/LlamaIndex, Hugging Face
Search, Retrieval & Vector Databases
Hands-on with vector databases (Qdrant/Milvus/ElasticSearch), semantic search, and rerankers
Practical expertise in chunking strategies (semantic, layout-aware) and embedding selection/tuning
Document Processing:
Experience processing complex documents: table extraction, layout parsing, OCR, and multimodal LLM-based image description/structure detection
Integrations & Cloud:
Experience integrating tools and data sources via protocols like MCP (or similar agent-tool frameworks)
Solid prompt engineering and cloud deployment (AWS/Azure/GCP), containers, and CI/CD
Analytical & Delivery
Proven ability to evaluate and prioritize opportunities, with strong analytical thinking and structured problem-solving skills
Experience working in an agile or iterative delivery environment, with the ability to manage competing priorities and adapt to changing requirements