Director of Engineering

About Triomics

Triomics is building the agentic AI layer for oncology EHRs. Cancer hospitals spend billions on highly trained staff manually reading unstructured patient records - pathology reports, clinical notes, genomic panels - to power workflows like trial matching, registry curation, visit prep, and quality reporting. We replace that manual work with task-driven AI agents that sit inside the EMR and process records at scale, in real time.

Our platform is trusted by leading cancer centers including Memorial Sloan Kettering, Mount Sinai, and Yale Cancer Center. We have grown 10x in the last year and process millions of oncology medical documents monthly.

Our investors include Battery Ventures, Lightspeed, General Catalyst, Nexus Venture Partners, and Y Combinator.

The Role

We have live deployments at some of the best cancer centers in the world, and multiple products in production at scale.

We are looking for a Director of Engineering to own that. You will run all of product and platform engineering - the application teams behind the platform, infrastructure, and reliability function; and frontend. The engineering leads across these areas will report to you.

You will report to the CTO and take day-to-day ownership of how engineering plans, builds, ships, and operates.Your job is to raise the bar. This is not a hands-off role. You'll set technical direction, sit in design reviews, get into production incidents, and solve problems for strong senior engineers - while building the process, and standards that let a ~20-person team ship like a much larger one.

What You'll Own

All engineering execution. Application engineering, platform and infrastructure, reliability, and frontend. You own what ships, when it ships, and how good it is.

Production reliability and quality. Our customers are clinicians making care and research decisions on our output. Every error erodes trust, and clinical users don't give second chances. Own the observability across multi-tenant deployments, catching pipeline failures and data-quality regressions before customers do, incident response, and a real testing and code-quality culture.

Customer go-lives. Onboarding a new cancer center is high-stakes. Make deployment to new customer environments - across multiple clouds and private/single-tenant setups, each with its own security and compliance requirements - fast, repeatable, and boring.

The engineering operating system. Planning and execution cadence, design and code review, release process, on-call, and the bar for what "done" means. Replace heroics and tribal knowledge with systems.

The team and the bar. Set leveling and promotion standards, run performance honestly, and hire across the org as we scale. Define the structure as the team grows from a handful of pods into a real engineering organization.

Partnership with ML and Product. Work with the ML team on serving, evaluation, and accuracy benchmarks, and with Product on turning strategy into reliable, shippable software.

What Success Looks Like in the First 90 Days

Days 1–30: Learn the systems, the products, the team. Read the architecture and the code. Use every product. Look at raw extraction output against source documents and understand where the platform is fragile and why. Sit in on a customer deployment and a production incident. Meet every engineer, every lead, and the ML and product leadership. By the end of month one you should be able to name the three things most hurting reliability and delivery speed, and have a candid read on the strengths and gaps of the engineering team and its leads.

Days 30–60: Take ownership and set the operating system. Take over the day-to-day running of engineering from the CTO - planning, reviews, prioritization, and delivery accountability. Stand up the operating cadence: how teams plan and commit, how code and designs get reviewed, how releases ship, and how incidents are handled. Pick the single biggest reliability or delivery problem and personally drive it to a fix, so the team sees the new bar rather than just hearing about it.

Days 60–90: Show the bar moving and stand up the plan. Demonstrate measurable improvement on reliability and release quality, and a faster, more standardized path to customer go-live.

What You'll Bring

• 12+ years building production software, with at least 4+ years managing engineers - including managing leads or managers, not just individual contributors.
• Track record of running engineering for a multi-team or multi-product B2B SaaS company, ideally data-intensive, and taking products from fragile to genuinely production-grade at scale.
• Real technical depth. You can reason about architecture, review a design, and debug a production issue. Strong senior engineers respect you because you understand the system, not just the org chart.
• Hands-on experience with multi-tenant cloud (AWS and/or Azure), Kubernetes, CI/CD, and data- or document-heavy backend systems - and the judgment to know where reliability actually breaks.
• Built engineering process and quality culture from a low baseline in a fast-moving environment - testing, observability, release discipline, incident response - without grinding delivery to a halt.
• A record of hiring, leveling, and developing engineers and managers, and of setting and holding a high bar for what shipped software looks like.
• Clear, direct communication. You make hard calls with incomplete information, you push back when requirements are wrong, and you don't wait for permission. High agency, comfortable with ambiguity.
• Willing and able to work in-office in Bengaluru. This role runs a co-located team; presence is part of the job.

Bonus Points If…

• You have worked in healthcare, life sciences, or clinical data - particularly oncology, clinical trials, or regulated, high-stakes data products.
• You have run engineering for products where AI/ML accuracy is the core product value, not a feature bolted on the side - including model serving, GPU infrastructure, and evaluation pipelines.
• You have shipped and supported enterprise deployments in customer-controlled cloud or on-prem/private environments with serious security and compliance requirements.
• You have scaled an engineering organization through hypergrowth and lived through the structural and cultural breakpoints that come with it.
• You have hands-on familiarity with our stack - Java/Spring Boot, Python, React/TypeScript, PostgreSQL, Elasticsearch, and workflow orchestration like Temporal.

Why Join Us?

• Impact at scale. The systems your teams build directly power AI workflows that accelerate cancer research and improve patient outcomes.
• Cutting-edge problems. Hard, data-intensive systems at the intersection of AI, healthcare, and scale - in a highly regulated industry where reliability is non-negotiable.
• World-class team. Work alongside top talent across AI, engineering, and product, with best-in-industry compensation.
• Culture that ships. Fast-paced, ownership-driven, with company-sponsored workations.

Perks & Benefits

• Lunch provided at the office - one less daily decision.
• Flexible working hours - we care about output, not clock-ins.
• Comprehensive health insurance for you and your family.
• Zomato meal benefits for early starts and late nights.