Associate Tech Architect – GenAI Engineering

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Location: India (Bangalore/Mumbai)
Experience: 5–6 years
Reports to: Senior Architect – Machine Learning

About the Role

We are looking for a strong software engineer who is excited to go deeper into Machine Learning and Generative AI engineering.
If you have solid backend development skills and bring an ML X-Factor—anything that shows genuine interest, initiative, or capability in ML/GenAI—this role is designed for you.

Your ML X-Factor could be:

• self-initiated projects,

• hackathon wins,

• open-source contributions,

• PoCs you built at work,

• or any demonstrable evidence of curiosity and capability in ML/GenAI.

This is a 70% hands-on coding, 30% design role where you will learn, build, and shape internal GenAI solutions with guidance from the Senior Architect – ML.

• Build and maintain RAG pipelines (we will guide you on best practices).

• Develop agentic workflows using frameworks like Google Agent Development Kit.

• Integrate GenAI functionality into backend services using Python/FastAPI.

• Integrate LLMs with APIs, internal systems, and enterprise datasets.

• Work on embedding pipelines, simple ETL workflows, and vector databases.

• Help build evaluation, testing, and benchmarking workflows for GenAI outputs.

• Translate product requirements into technical designs and implementation plans.

• Participate in design discussions, code reviews, and best-practice engineering.

• Work closely with product and engineering teams to deliver GenAI features end-to-end.

• Deploy GenAI components using Docker, CI/CD, and GCP services.

• Learn to optimize for performance, cost, reliability, and scalability.

This role is ideal if you are:

• A Software Developer/Backend Engineer eager to transition into ML/GenAI.

• Someone with an ML X-Factor—a spark in ML/GenAI that shows potential, not necessarily years of formal experience.

• Excited about building systems end-to-end and growing into an architect-level path.

Open backgrounds include:

• Backend Engineers (Python/Java/Node)

• Full-stack developers

• ML engineers with strong coding fundamentals

No research experience required.

• Strong Python development experience (FastAPI is a plus).

• Solid fundamentals in API design, clean architecture, debugging, testing.

• Ability and eagerness to learn GenAI concepts and apply them in production.
   

You should bring at least one of the following:

• Basic experience with LLMs, RAG, embeddings, or vector databases

• Exposure to traditional ML solutions

• Experience with any orchestrators/agent frameworks (we will train you on Google ADK)

• Self-driven ML/GenAI projects, real-world PoCs, or hackathon achievements

• Experience with Version Control and modern development workflows.

• Any cloud exposure (GCP preferred but not mandatory).

• Comfort working with Docker and CI/CD is a plus.

• Ability to write clear technical documentation.

• Strong ownership, problem-solving, and learning mindset.

• Comfortable working in fast-paced, evolving environments.

• Experience with Pinecone/Chroma/Weaviate.

• Familiarity with Lang Chain/LlamaIndex.

• Exposure to ML pipelines or classical ML.

• Ideal opportunity for software engineers transitioning into GenAI.

• Work directly with a Senior Architect – ML and grow toward an architect role.

• Build real GenAI systems (RAG, agents, workflows) used across the organization.

• Work with cutting-edge GenAI, agentic orchestration, and LLM deployment stacks.