Designation: Manager

Level: L4

Experience: 10 to 12 Years

Location: Bengaluru

Job description:

We are looking for an experienced and highly autonomous AI Architect with a strong ownership mindset to join our team. As a Forward Deployed Architect, you will serve as a hands-on senior technical architect on the Applied AI Engineering team, owning the end-to-end design and delivery of AI-driven business transformation projects.

This role sits at the intersection of engineering execution, AI architecture, and enterprise governance. The FDA embeds directly with engineering and product teams to accelerate adoption, shape solution design, and ensure AI systems are scalable, secure, cost-efficient, and governed by design.

The individual will also play a critical role in building and operationalizing agentic engineering capabilities — including reusable agents, agentic workflows, and AI-augmented delivery patterns — enabling engineering teams to increase throughput and quality without proportional increases in headcount.

Responsibilities:

Work side by side with PMs, Business users and Architects to scope and deploy AI systems that actually solves problems.

Build and integrate systems using LLMs, RAG pipelines, agent frameworks, vector databases, and related tools.

Navigate real-world challenges: data access, authentication, security, networking, and brittle enterprise environments.

Translate high-level designs into working components that deliver measurable outcomes.

Debug relentlessly - optimize for reliability in production, not just elegance in code.

Write modular, reusable code that balances speed of delivery with long-term maintainability.

Embed with client engineering teams to accelerate adoption and integration.

Share insights from field implementations to inform reusable components in our platform.

Document decisions with clarity so internal teams can build on your work.

Own technical governance across AI initiatives, ensuring consistency, safety, and compliance.

Agentic squads:

Design and build agentic squads that augment existing engineering teams.

Create reusable AI agents (e.g., coding, testing, QA, observability, knowledge, operations) that can be adopted by squads with minimal friction.

Define standards for:

Agent orchestration

Human-in-the-loop controls

Observability and evaluation

Enable teams to integrate agents into their SDLC and delivery workflows.

Skills Required:

10+ years of engineering experience, with proven work shipping AI/ML systems into production.

Strong Python skills and deep familiarity with modern AI/ML frameworks (LangChain, LlamaIndex, Hugging Face, vector databases).

Hands-on with cloud deployment, orchestration, CI/CD, and distributed environments (AWS, Azure, GCP).

Ability to debug gnarly real-world issues (auth failures, networking black holes, flaky data pipelines).

Problem-solver who thrives in ambiguity, focused on delivery and reliability over process and ceremony.

Comfortable in client-facing environments - credible with engineers, clear with executives.

Prior Technical Architect experience in the AI space

Qualification: You have a Master’s degree in Computer Science, Data Science, AI, or a related field with a strong AI background.