AI Architect – Life Sciences

Aparajita Consultancy Services; Hyderabad, Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Aparajita Consultancy Services seeks an experienced AI software architect to own and evolve our enterprise reference architecture for generative and agentic AI. You will prototype, build proofs, and drive solutions from concept to production while shaping roadmaps and standards.

Deep hands-on capability across the modern AI stack is required, including orchestration, model serving, and governance. You will mentor engineers and communicate with senior leadership to align technical decisions with

Qualifications

• 8+ years in software/AI engineering with production delivery of agentic, generative and ML/DL systems.
• Hands-on depth across the modern agentic stack and orchestration frameworks.
• Experience in evaluating guardrails and measurable model quality.
• Ability to design end-to-end architectures with cloud and data-platform depth.

Responsibilities

• Own the architecture and evolve enterprise reference architecture for generative AI.
• Prototype in code, build proofs, and demonstrate capabilities.
• Lead solutioning from POC to production and set roadmaps.
• Stand up AI platform components including model serving and orchestration.
• Embed governance by design with traceability and tenant isolation.

Skills

AI engineering

Software architecture

Lead & mentoring

Communication

Tools

LangGraph

Dapr Agents

RAG

Graph databases

vLLM

LLMOps

Databricks

AWS

Azure

Neo4j

Job description

WHAT YOU'LL DO

• Own the architecture, and make it easy to build on.
• Own and evolve our enterprise reference architecture for generative and agentic AI across models, retrieval, orchestration, reasoning, and the governance that runs through all of it.
• Build and demonstrate, hands-on.
• Prototype in code, stand up working proofs and demos, and stay close to the models and tools leading by showing, and learning continuously as the field moves.
• Build reusable frameworks, blueprints, and paved-road patterns that engineering and product teams adopt.
• Lead solutioning from proof-of-concept to production: scope experiments, prove them, and build the roadmap to scale.
• Stand up the shared AI platform and enablement model serving, vector and graph retrieval, tool and agent orchestration, observability, and evaluation and help teams build on it safely.
• Embed governance by design: traceability, human-in-the-loop, evaluation, and tenant isolation built into every architecture from the start.
• Own build-vs-buy decisions and set technical standards; run architecture reviews and mentor engineers.
• Translate technical trade-offs clearly for leadership, clients, and engineering.

WHAT YOU'LL BRING

• Production-proven, end to end.
• Deeply hands-on you still build.
• 8+ years in software / AI engineering, with production-proven delivery of agentic, generative, and classical ML/DL systems not just POCs.
• Hands-on depth across the modern agentic stack: orchestration frameworks (e.g.
• LangGraph, Dapr Agents), protocols (MCP; familiarity with A2A), RAG and GraphRAG, vector and graph databases (e.g. Neo4j, pgvector), model serving (e.g.
• vLLM), and LLMOps (versioning, drift, cost, evaluation).
• Practical evaluation and guardrails experience making model quality measurable and defensible.
• Command of the full span from classical ML/DL to generative to agentic, and the judgment to choose the simplest approach that works.
• Cloud and data-platform depth (AWS / Azure / Databricks) and familiarity with semantic layers and lakehouse architectures.
• End-to-end architecture ownership and the ability to set and evolve standards across an organisation.
• Excellent communication and stakeholder management, including with senior leadership, and a track record of mentoring.