AI/ML Architect New India

66degrees; India; Sur place; INR 3 500 000 - 6 000 000; Plein temps

Résumé du poste

66degrees is seeking an AI/ML Architect in India to design and ship production AI systems for enterprise clients. You will lead engineers, own architecture, and stay with the system through production while engaging clients directly.

Projects run 12–16 weeks and involve AI, ML, and data across cloud infrastructure. The role is hands-on and client-facing, requiring deep technical expertise, strong communication, and a track record of delivering end-to-end AI solutions on Google Cloud.

Qualifications

• Has designed and shipped production ML or AI systems and owned them post-launch.
• Deep foundation in multiple techniques with real business impact.
• Built a generative/agentic AI system with production-grade architecture and cost/latency handling.
• Production fluency on a hyperscaler, preferably Google Cloud; AWS/Azure is acceptable with translation.
• Strong software engineering: Python, SQL, containers, CI/CD; hands-on with recent code.

Responsabilités

• Design architectures for engagements: data pipelines, ML, AI agents, and production path on Google Cloud.
• Write and review core logic, orchestration, evaluation; ensure reliable production readiness.
• Own production deployments, monitoring, drift, retraining, and incident response.
• Lead engineers, provide clear briefs, review work, and mentor growth.
• Manage client discovery, define scoped plans, present designs, and manage risk with options.

Connaissances

Generative AI

Agentic AI

Python

SQL

CI/CD

Google Cloud

Hands-on Architect

Leadership

Formation

Bachelor's degree in computer science, data science, engineering or related field

Outils

Cloud platforms (GCP)

CI/CD tooling

Description du poste

66degrees is an end-to-end AI transformation partner that guides enterprises from complex business challenges to clear, quantifiable outcomes. Our company is the culmination of several successful firms, each a leader in its own right in cloud, artificial intelligence, and data. This convergence of talent and expertise is how we help businesses reach their own "inflection point," where chaotic data becomes a strategic asset, complexity becomes clarity, and AI becomes an engine for growth. Our ultimate vision is to be the catalyst for a future where every business operates as an intelligent enterprise, with autonomous systems unlocking human potential.

At 66degrees, we believe in thriving through challenges and winning together. These values not only guide us in achieving our goals as a company but also for our people. We are dedicated to creating a significant impact for our employees by fostering a culture that sparks innovation and supports professional and personal growth along the way.

Overview of Role

An AI/ML Architect at 66degrees designs and ships production AI systems for enterprise clients and leads the engineers who build them. The Architect is the senior technical person on an engagement: the primary technical point of contact for the client, the owner of the architecture, and the person the team takes direction from.

The role is hands‑on and client‑facing in equal measure. Architects take a business problem, define the solution and the value it delivers, and then build and deploy it. They write and review code, make the architectural decisions, and stay with the system through production. They also run discovery, present to client executives, and are the face of 66degrees on the engagement.

This role is based in India and works daily with US‑based colleagues and clients. Engagements typically run 12 to 16 weeks and are delivered by a Delivery Manager, one or more Architects, and a team of engineers.

Why this role

2026 Google Cloud AI Partner of the Year. This team's work won the Artificial Intelligence category this year, one of four Partner of the Year awards 66degrees has earned. You're joining the top of the Google Cloud AI ecosystem

About 60% of the work is generative and agentic AI, in production, for clients up to the Fortune 10. The rest is classical ML and MLOps, so you build real agents without losing the rest of the craft.

New problem, new client, every 12 to 16 weeks. You build range fast and never spend three years on one system

The whole stack. Architects span infrastructure, software, data, ML, AI, and analytics. The role is built to make you a well‑rounded technologist, not to keep you in one lane

Player‑coach all the way up. Growth here doesn't mean giving up the craft. Leaders still build, and the management track is open because the team keeps growing, not because someone has to leave

No up‑or‑out, no partner‑track politics. Nobody is competing to differentiate themselves; everyone is trying to be the best technologist in the room, which is why people share what they know

The team has grown roughly tenfold in three years and people stay. The few who've left went on to top tech firms and AI startups

Responsibilities

Build

Design the architecture for each engagement: data pipelines, classical ML, agentic and generative AI, and the production path on Google Cloud, with the trade‑offs written down

Write and review the code that matters: core logic, orchestration, evaluation, the parts an engineer shouldn't be guessing at

Take systems to production and own them through handoff: deployment, monitoring, drift, retraining, incident response, and a client who can run it after we leave

Choose the right approach for the problem, and defend it on cost, explainability, and fit rather than on what's fashionable

Lead the team

Direct a team of engineers: write the brief with the reasoning, not only the tasks; confirm it landed before code is written; review the work

Run a team where engineers raise problems early and are heard when they do

Develop engineers: pairing, giving them the client call, making them present the design review, and telling the Delivery Manager who is ready for more

Delegate real work and still own the hard parts. Not a solo builder; not a delegator who only checks in

Own the client relationship

Run discovery: turn an ambiguous ask into a scoped plan with success criteria the client agrees to

Hold the solution to what the client actually needs, and when scope and need diverge, raise it early with options and what each costs

Raise risk the day you see it, up and across, in business terms, with options. Report "on track" only when it is

Present to client executives: the design, the trade‑offs, the status, and the recommendation, answer first

Spot expansion: where the client's next problem is, and tell sales

Qualifications

Technical (required)

Has personally designed and shipped production ML or AI systems, more than once, and owned them after launch. This is a hard requirement: an Architect who cannot point to systems they built and ran is not an Architect, whatever else is on the resume

A data science foundation with range: several technique families (classification, forecasting, NLP, deep learning, recommendation, anomaly detection) each tied to a real business outcome. Depth in a few, breadth across the rest

Has built a generative or agentic AI system that real users depended on: the architecture end to end, where the tools ran, how cost and latency were handled, and how quality was measured. A serious RAG system or single‑agent workflow with real evaluation discipline qualifies; a chatbot demo does not

Production fluency on a hyperscaler: Google Cloud preferred (Vertex AI, BigQuery, Cloud Run or GKE); deep AWS or Azure experience with a credible translation is acceptable

Strong software engineering: expert Python and SQL, containers, CI/CD, and the habits that make code someone else can run

Currently hands‑on, with recent, specific examples of code written and architectural decisions made

Leadership and delivery (required)

Currently leads a team of engineers or data scientists, delegating real work while owning the architecture and core logic

A repeatable method for taking an engagement from discovery through handoff: phases, milestones, who does what, validation before anything ships

A track record of reshaping scope when the original ask wasn't the right solution, and of making the business case for the change

Communication and judgment (required)

Answers the question asked, first, then the detail. Adjusts depth for the audience: can explain a system to an engineer and to a CFO in the same hour

Executive presence: speaks with conviction, holds a position under challenge, and is someone we would put in front of a client executive next week without coaching

Raises risk before it becomes a problem, to the person who can act on it, with a proposed fix. Comfortable disagreeing with senior people when the work calls for it

Comfortable operating with autonomy across a significant time‑zone gap with US colleagues and clients

Education

Bachelor's degree in computer science, data science, engineering or a related field, or equivalent experience

Preferred

Consulting or professional services background, with fluency in SoWs, scope, and billable delivery

Google Cloud certifications, or delivery alongside Google teams

Experience with agentic frameworks and patterns in production: tool calling, state management, MCP, multi‑step orchestration, policy‑guarded loops

Regulated‑industry delivery (financial services, healthcare) where explainability and audit are requirements, not features

Daily use of AI coding assistants and agents in your own work, with a view on where they help and where they get in the way

Experience working with a US‑based team from India, and a point of view on how to make it work

What the job demands

The client sees you. You present the design, you deliver the bad news, you defend the recommendation. The strength of the 66degrees brand on an engagement is the Architect leading it

The plan will be wrong sometimes. Client problems rarely arrive fully defined, and scope moves. Working out what's really needed and saying so is the job, not an exception to it

Your engineers learn from you. If you raise risks, they will. If you don't, they won't. You set the standard for how the India team works

The US is asleep for half your day. You will make decisions with incomplete direction and own them. This role works a shifted schedule: online through 2:00 PM US Eastern (11:30 PM IST), so that most of the US working day overlaps with yours

It's hands‑on. If your week has become meetings and status calls, this is not the role

About 66degrees and the AI/ML practice

66degrees is a leading consulting and professional services company specializing in developing AI‑focused, data‑led solutions leveraging the latest advancements in cloud technology. With our unmatched engineering capabilities and vast industry experience, we help the world's leading brands transform their business challenges into opportunities and shape the future of work.

At 66degrees, we believe in embracing the challenge and winning together. These values not only guide us in achieving our goals as a company but also for our people. We are dedicated to creating a significant impact for our employees by fostering a culture that sparks innovation and supports professional and personal growth along the way.

The AI/ML practice spans roughly 100 specialists across the U.S., Canada, the UK, France, and India, working across three pillars: agentic and generative AI; classical ML; and MLOps and AgentOps. The India team is being built to own engagements end to end, with a path from Engineer to Architect that runs through India.

Please note, we cannot sponsor or transfer any visas, of any kind, at this time.

66degrees is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race, color, religion, sex, gender, gender identity, national origin, age, weight, height, marital status, sexual orientation, veteran status, disability status or other legally protected class.

AI Transparency & Disclosure

As an AI transformation partner, 66degrees leverages intelligent solutions to enhance our recruitment experience. We utilize AI tools—including LinkedIn Recruiter’s Hiring Assistant and interview transcription technologies to assist with sourcing, role analysis, and capturing interview highlights.

These tools augment our process, but we "Commit to Our Craft" by ensuring all final hiring decisions are made by our human Talent Team. By applying, you acknowledge the use of these technologies to help us "Win Together" in finding the best fit for our team.