Senior AI/ML Engineer — Agentic Systems
Experience: 4–8 years | 2+ years with LLMs in production
Location: Office – Coimbatore/Bengaluru
About Aivar Innovations
Aivar is an AI -first technology partner where cutting -edge technology meets industry expertise to supercharge your projects. Our AI -augmented teams accelerate development, reduce time -to -market, and deliver exceptional code quality. We bring together the best minds in tech to craft scalable, repeatable solutions that drive real momentum for your business.
Technical Focus
Own accelerators’ intelligence core: the governance processing engine, multi -agent document extraction, knowledge graph construction, LLM orchestration, and the Evals Engine for cross -model benchmarking. Ship production systems processing 100K+ enterprise documents.
Functional Expectations
- Build the governance engine — reasoning against business rules, compliance validation with green/red -line thresholds, and action execution
- Design multi -agent orchestration across the 6 -n stage pipeline with structured reasoning chains and tool -use patterns
- Implement multi -format document extraction (PDF, TIFF, JPG, structured data) using OCR, layout analysis, and table extraction models
- Build the decision graph / context graph that accumulates institutional knowledge from human -in -the -loop interventions
- Develop the Evals Engine for A/B testing across LLM providers (GPT -4, Claude, Llama, Mistral) with regression testing
- Implement responsible AI guardrails — bias detection, confidence calibration, explainability layers
Optimize inference cost and latency through quantization, caching, and intelligent model routing
Must -Have Technical Skills
- Production LLM experience —Anthropic, Bedrock APIs + open -source models (Llama, Mistral)
- Agentic frameworks — Strands Agents, LangChain, LangGraph, CrewAI, AutoGen, or custom multi -agent systems
- Document AI — OCR, layout parsing (LayoutLM), table extraction, Textract/Unstructured.io
- Vector databases — OpenSearch, Pinecone, Weaviate, pgvector; RAG architecture design
- Strong async Python engineering — production -grade, not notebook -level
- AWS ML services — SageMaker, Bedrock, Lambda, S3, EKS
- Model evaluation methodologies — accuracy metrics, A/B testing, LLM regression suites
Core Tech Stack
Python, FastAPI, LangChain/LangGraph, Ray, OpenAI/Anthropic/Bedrock APIs, Hugging Face, Pinecone/Weaviate/pgvector, Tesseract/LayoutLM/Textract, Prometheus/Grafana, AWS (SageMaker, Bedrock, Lambda, S3)