Agentic AI Engineer – Azure | LLM | RAG | LangGraph

ApTask; Bengaluru; On-site; INR 3,800,000 - 7,000,000; Full time

Job summary

ApTask seeks an experienced Agentic AI Engineer to lead end‑to‑end design, productionisation and operationalisation of LLM‑based solutions on Azure. You will act as the technical face to clients while guiding a cross‑functional delivery team.

The role focuses on architecting Agentic AI systems, RAG pipelines, and robust model deployment with strong governance, security and explainability. You will own CI/CD pipelines and collaborate with product, data engineering and security teams in a hybrid

Qualifications

• 6+ years in software engineering or AI with hands-on production experience.
• Deep experience with LLMs and RAG architectures: retrieval design and embeddings.
• Proven record in fine-tuning LLMs (LoRA, full fine-tune) and prompt engineering.
• Expertise with agentic frameworks and orchestration (LangChain, LangGraph).
• Experience with production MLOps/ModelOps and model registries.
• Strong data engineering basics and data privacy controls.
• Security and compliance mindset for sensitive data domains.

Responsibilities

• Architect and build Agentic AI systems: orchestrate agents, action executors, and retrieval layers.
• Design and implement LLM solutions (RAG, retrieval chains, prompts) for production use.
• Own model deployment, serving and scaling on Azure (Azure AI/ML, AKS) and hybrids.
• Build MLOps pipelines: CI/CD for models, automated testing, monitoring, drift detection.
• Lead data pipelines for retrieval: vector stores, semantic search, embeddings, privacy controls.
• Implement model explainability, confidence scoring and prompt security.
• Define governance: versioning, reproducibility, lineage and audit trails.
• Collaborate across product, data engineering, security, DevOps and UX.
• Mentor engineers; conduct reviews and pair programming; recruit when needed.
• Serve as primary technical contact for clients: designs, architecture reviews, RFP support.

Skills

LLMs & RAG

LangChain

LangGraph

Azure Platform

MLOps

Vector DBs

Prompt Engineering

Data Privacy & Security

CI/CD

Tools

Azure ML

AKS

Container Registries

Prometheus/Grafana/ELK

Job description

Job Title :- Agentic AI Engineer – Azure | LLM | RAG | LangGraph

Job Type:- FTE

Job Summary:

We are seeking an experienced, hands‑on AI (3+ years) to lead technical delivery and client engagement for Agentic AI platforms. The role owns end‑to‑end design, productionisation and operationalisation of LLM‑based solutions (RAG, fine‑tuning, model serving) on Azure, and will act as the technical face to the client while leading a cross‑functional delivery team.

What Success Looks like:

• Deliver production Agentic AI features that meet SLA targets for latency, throughput and reliability.
• Reduce time‑to‑value for LLM integrations via repeatable patterns, MLOps pipelines and reusable components.
• Maintain model governance, explainability and security posture appropriate for sensitive data domains.

Key Responsibilities:

• Architect and build Agentic AI systems: orchestrate agents, action executors, retrieval layers, and feedback loops.
• Design and implement LLM solutions (RAG, retrieval chains, prompt engineering, fine‑tuning/LoRA/P-tuning) for production use.
• Own model deployment, serving and scaling on Azure (Azure AI, Azure ML, AKS, container registries) and hybrid setups.
• Build MLOps & ModelOps pipelines: CI/CD for models and services, automated testing, monitoring, drift detection and rollbacks.
• Lead data pipelines for retrieval: vector stores, semantic search, indexing, embeddings, data privacy & access controls.
• Implement model explainability, confidence scoring, adversarial protections and prompt security (prompt injection mitigation).
• Define and enforce model governance: versioning, reproducibility, lineage, audit trails and compliance.
• Collaborate with product, data engineering, security, DevOps and UX to ensure integrated delivery and acceptance.
• Mentor and upskill engineers; conduct technical reviews and pair programming; recruit when required.
• Act as primary technical contact for clients: present designs, lead architecture reviews, and support RFP/interview processes.

Required Skills & Experience:

• 6 + years in software engineering/AI with demonstrable, hands‑on production experience.
• Deep experience with LLMs and RAG architectures: retrieval design, vector DBs (Pinecone/Weaviate/Milvus), embeddings.
• Proven track record in fine‑tuning/customising LLMs (LoRA, full‑fine tune, instruction tuning) and prompt engineering.
• Expertise in Agentic frameworks and orchestration (LangChain, LangGraph, custom agent frameworks).
• Production MLOps/ModelOps: CI/CD for models, model registry, automated testing, monitoring (Prometheus/Grafana/ELK), drift detection.
• Data engineering basics: SQL/NoSQL, ETL, schema design, data lineage and data privacy controls.
• Security & compliance: secrets management