SENIOR AI ENGINEER

AI Innovation and Inclusion Initiative (A4I); Bengaluru; On-site; INR 2,800,000 - 4,200,000; Part time

Job summary

AGENTIC SYSTEMS is seeking a Senior AI Engineer to design and scale agentic AI systems for social impact within the A4I Lab initiative. The role emphasizes architectural leadership, production readiness, and cross-functional collaboration across multilingual and low-resource environments.

You will shape scalable AI platforms, guide deployment patterns, and mentor engineers while delivering high-value, responsible AI solutions for education, healthcare, and inclusivity.

Qualifications

• Must design production-grade AI systems with end-to-end agentic workloads.
• Hands-on with agent orchestration frameworks such as LangGraph, LlamaIndex, or n8n.
• Strong understanding of LLM applications, RAG, embeddings, and grounding.
• Cloud/Platform engineering experience including containers, CI/CD, model lifecycle, and monitoring (Azure valued).
• Design systems for scale, balancing performance, cost, resilience, and usability.
• Fluency in Python for production environments with maintainable code.
• Track record in guiding architecture decisions and mentoring engineers across teams.

Responsibilities

• Lead the architecture of end-to-end agentic AI systems from prototype to production.
• Build intelligent platforms integrating LLMs, retrieval, data, and multi-modal inputs.
• Define deployment standards, monitoring, versioning, and MLOps practices for safe production rollout.
• Provide technical leadership and mentoring across engineers, researchers, and stakeholders.

Skills

Production AI Architecture

Agentic Systems Orchestration

LLM Retrieval & Knowledge

Cloud & Platform Engineering

Systems Thinking at Scale

Python Engineering

Technical Leadership

Education

BS/MS in CS/EE/Math

Tools

LangGraph

LlamaIndex

n8n

Azure OpenAI

Ollama

vLLM

Hugging Face

LLaMA

Mistral

Phi

Job description

AGENTIC SYSTEMS

Organization: A4I Lab (IIIT-B × Microsoft)

Location: IIIT Bangalore

Type: Contract (through March 2027, extendable)

Experience: 6 to 8 years

About A4I Lab AI Innovation and Inclusion Initiative (A4I) is a partnership between Microsoft and IIIT-B, collaborating with non-profit partners to harness AI for solving real-world challenges in education, healthcare, accessibility, and agriculture. A4I evolves innovations into open-source Digital Public Goods (DPGs) that are deployable at scale, fostering a strong AI innovation ecosystem for social impact.

The Opportunity A4I Lab is seeking an experienced Senior AI Engineer to help design and scale agentic systems to drive meaningful public and social impact. This role is suited to someone who combines strong architectural judgment with hands‑on technical depth and is comfortable building for real‑world operating conditions, such as multilingual use cases, constrained environments, and diverse stakeholder needs. You will shape production-ready AI platforms and multi‑agent workflows that can serve high‑volume, high‑value use cases across sectors such as education, healthcare, agriculture, and accessibility. The role offers the opportunity to guide architecture from early design through deployment, while helping create scalable and reusable Digital Public Goods.

What You Will Be Doing

• Lead the Architecture of Agentic AI Systems: Design end‑to‑end agentic AI architectures that move from prototype to production, with a strong focus on reliability, scalability, and practical deployment. You will translate complex social‑impact use cases into systems that are robust, auditable, and suited to real‑world operating conditions, including multilingual and low‑resource environments.
• Build Intelligent, Integrated AI Platforms: Shape AI platforms that bring together LLMs, retrieval systems, structured and unstructured data, and multi‑modal inputs such as speech, documents, and vision. You will guide the design of RAG pipelines, knowledge layers, model integration patterns, and evaluation approaches that improve system quality in meaningful ways.
• Drive Production Readiness and Platform Maturity: Define architectural standards for deployment, monitoring, versioning, and safe rollout across cloud‑based AI systems. You will help establish sound engineering and MLOps practices so that new capabilities can move into production with consistency, traceability, and operational confidence.
• Provide Technical Leadership Across Teams: Work closely with engineers, researchers, and partner stakeholders to guide technical decisions, clarify trade‑offs, and keep execution aligned with the overall system vision. You will mentor team members, support strong technical documentation, and help build reusable open‑source assets that strengthen A4I’s Digital Public Goods approach.

Role Scope

• This is a hands‑on architecture role with meaningful technical leadership and close involvement in engineering decisions.
• The work focuses on production‑oriented AI systems and reusable platforms that create clear social value.
• You will work across multiple stakeholders and use cases, while remaining closely connected to delivery and implementation.

Must‑Have Skills

• Production AI Architecture: Demonstrated experience designing and shipping production‑grade AI systems, including at least one end‑to‑end agentic or LLM‑powered workload used by real users. You should be comfortable thinking beyond prototypes and designing for reliability, scale, maintainability, and operational clarity.
• Agentic Systems and Orchestration: Hands‑on experience with one or more agent orchestration frameworks such as LangGraph, LlamaIndex, n8n, or comparable tools. You should understand how to structure multi‑step workflows, tool use, memory, and coordination patterns in a way that is practical for production systems.
• LLM, Retrieval, and Knowledge Systems: Strong understanding of LLM application design, including RAG architectures, vector retrieval, embeddings, context management, and evaluation. You should be able to make sound design choices around retrieval quality, grounding, and domain‑specific performance.
• Cloud and Platform Engineering: Good experience working with cloud platforms and production deployment patterns, including containerization, CI/CD, model lifecycle practices, and operational monitoring. Comfort with Azure is especially valuable, though experience across AWS or GCP is also relevant.
• Systems Thinking at Scale: Ability to design systems for meaningful scale, balancing performance, cost, resilience, and usability under real‑world constraints. This includes an appreciation of how architecture decisions affect maintainability, team velocity, and long‑term platform evolution.
• Strong Python Engineering: Fluency in Python for production environments, with a focus on clean, testable, maintainable code. This role requires engineering discipline, not just experimentation or scripting.
• Technical Leadership: A track record of guiding architecture decisions, mentoring engineers, and working effectively across cross‑functional teams. You should be able to communicate clearly with both technical and non‑technical stakeholders and help move teams toward sound implementation choices.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or equivalent demonstrated expertise.
• 6 to 8 years of experience designing and building software systems, including at least 2 years focused on production AI or ML applications.
• Demonstrated experience in architecting and deploying large‑scale AI platforms.
• Comfort working in multi‑stakeholder environments such as NGOs, academia, government‑linked programs, or enterprise settings.

Preferred Qualifications

• Experience adapting smaller or open models such as Llama, Mistral, or Phi for domain‑specific tasks, including PEFT, LoRA, or instruction tuning.
• Hands‑on exposure to VLMs, speech models, and multilingual or Indic‑language pipelines.
• Familiarity with both Azure OpenAI services and open‑source deployment options such as Ollama, vLLM, or Hugging Face.
• Prior work in social impact, public sector, or resource‑constrained settings where reliability and usability matter deeply.
• Experience with AI evaluation frameworks such as RAGAS, LangSmith, or custom evaluation approaches.
• Contributions to open‑source AI projects, technical publications, or applied ML work.

A4I Lab is committed to building AI systems that serve everyone. We actively encourage applications from candidates of all backgrounds, disciplines, and geographies.