Senior Director, AI Engineering

Cornerstone Research; Hyderabad; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Cornerstone OnDemand is seeking a Senior Director of AI Engineering to lead the Hyderabad-based AI Engineering organization. You will own the people, the technical direction, and the delivery outcomes for multiple AI teams building Workforce AI models and platforms that power skills inference, recommendations, and content understanding.

You will shape AI architecture, evaluate strategies, and drive cost-aware, scalable production systems while building an India talent bench and partnering with

Qualifications

• 15+ years in software engineering, with 7+ years leading engineering teams, including managers.
• Proven track record shipping AI/ML or Generative AI systems to production at scale in a product company.
• Deep technical credibility in AI engineering: LLM applications.

Responsibilities

• Lead and grow the India AI Engineering organization with 2-3 teams (15–30 engineers).
• Own the AI architecture and technical strategy for Workforce AI in India, including evaluation practices and cost/latency trade-offs.
• Deliver AI products at scale with multi-quarter roadmaps and cross-functional partner collaboration.
• Partner globally with US teams to align strategy and ownership across sites.

Skills

AI leadership

Software engineering

Team building

AI architecture

Cloud cost optimization

Cross-functional collaboration

Tools

Bedrock

SageMaker

LLM frameworks

Job description

We're looking for a

Senior Director, AI Engineering

This role is Office Based, Hyderabad Office

Senior Director, AI Engineering:

Experience: 15+ years in software engineering, including 7+ years leading engineering leaders and teams,and 4+ years delivering production AI/ML or Generative AI systems
Reports to: [VP / SVP, AI Engineering]
Scope: 2-3 engineering teams (~15-30 engineers) in Hyderabad, led through Engineering Managers and Tech Leads, with a mandate to grow
Shift: General shift, withregular evening overlap with US Eastern and Pacific time zones.

About Cornerstone OnDemand:

CornerstoneOnDemand helps organizations of every size develop, engage, and retain their people through a unified talent experience platform. Our software supports morethan 7,000 customers and tens of millions of learners worldwide. The Indiaengineering organization is a core part of Cornerstone's global productengineering, and our AI Engineering organization builds the Workforce AI capabilities and shared platform that power skills intelligence, contentintelligence, personalization, and agentic experiences across Cornerstone'sproducts.

About the role:

We are hiring a Senior Director, AI Engineering to lead Cornerstone's AI Engineering organization in Hyderabad. You will own the people, the technical direction, and the delivery outcomes for multiple AI engineering teams building the Workforce AI models, services, and platform that make Cornerstone's products intelligent - skills inference, recommendations,content understanding, retrieval-augmented generation, evaluation, and theagentic workflows layered on top.

This is a deeply technical leadership role. You will lead through managers and tech leads, but you are expected to be credible in the room: shaping AI architecture, pressure-testing retrieval and evaluation strategy, questioning inference cost and latency trade-offs, and reading a design document or a pull request with real judgment. You will not be writing production features day to day, but the quality of your technical instincts will set the ceiling for the organization.

You will also be one of Cornerstone's most senior AI voices in India - a genuine peer to AI Engineering leadership in the US, accountable for globally distributed ownership of real product surfaces rather than delegated execution. Building the AI talent bench in Hyderabad, and doing it responsibly with sensitive workforce data, is central to the job.

In this role you will…

Lead and grow the India AI Engineering organization

• Lead 2-3 AI engineering teams (~15-30 engineers) through Engineering Managers and Tech Leads - setting direction, clarifying ownership, and holding a high bar for both delivery and craft.
• Develop the leaders who report to you: coach managers on hiring, performance, feedback, and technical judgment, and build a succession bench so the organization is not dependent on any single person.
• Design the team topology - how AI product, platform, and applied research responsibilities are split so teams have clear, durable ownership and minimal hand-off friction.
• Create an environment where strong engineers do their best work: focused roadmaps, low process overhead, honest retrospectives, and visible career growth.

Own the technical direction for Workforce AI in India

• Set and defend the AI architecture and technical strategy for the systems your teams own - model selection and hosting, retrieval and RAG design, vector and feature stores, agent orchestration, and inference patterns.
• Establish rigorous evaluation and quality practices for AI systems: offline and online eval harnesses, golden datasets, regression gates, human-in-the-loop review, and quality metrics tied to customer outcomes.
• Drive build-vs-buy decisions across foundation models, AWS-native AI services (Bedrock, SageMaker), and third-party tooling - with a clear-eyed view of cost, lock-in, latency, and differentiation.
• Own cloud and cost accountability for AI workloads on AWS: inference cost per request, GPU and token spend, caching and model-routing strategy, rightsizing, and FinOps discipline.
• Lead architecture and design reviews personally, and raise the standard for how the organization writes design documents, reasons about trade-offs, and validates assumptions before building.
• Keep the platform and product layers healthy together - shared services, SDKs, observability, and CI/CD that let AI product teams ship quickly and safely.

Deliver AI products at scale

• Own end-to-end delivery for your teams' commitments: multi-quarter roadmap, dependency management, realistic sequencing, and predictable shipping without heroics.
• Partner with Product Management, Design, Data, Security, and SRE to turn ambiguous problem statements into shipped, measurable AI capabilities.
• Move AI work from promising prototype to durable production system - reliability targets, monitoring, graceful degradation, rollback, and on-call ownership.
• Make disciplined trade-offs between customer-visible quality, delivery speed, and long-term platform investment, and explain those trade-offs credibly to executives.

Partner globally with US teams

• Operate as a peer to AI Engineering, product, and architecture leaders in the US - jointly owning strategy rather than receiving it.
• Negotiate clear charter and ownership boundaries across sites so India-based teams own meaningful, end-to-end product surfaces and are accountable for outcomes.
• Maintain a workable overlap rhythm with counterparts in US Eastern and Pacific time zones, and design async-first practices - written proposals, decision records, recorded demos - so progress does not depend on meeting time.
• Represent India AI Engineering in global planning, architecture councils, and executive reviews, and bring back context that helps your teams make better local decisions.

Build the talent brand and AI bench in Hyderabad

• Own the AI hiring mandate for Hyderabad: workforce planning, sourcing strategy, interview loop design, calibration, and closing senior candidates.
• Raise the technical interview bar for AI roles - practical system design, applied ML and LLM depth, evaluation thinking - and train interviewers to assess it consistently.
• Strengthen Cornerstone's employer brand as an AI destination in Hyderabad through meetups, conference talks, technical blogs, open-source contributions, and university and intern programs.
• Build internal capability alongside external hiring: upskilling paths for engineers moving into AI work, mentorship structures, and a credible senior technical ladder in India.

Responsible AI, trust, and compliance

• Own responsible AI practice for your organization - bias and fairness testing, explainability, human oversight, model and data documentation, and clear escalation paths.
• Ensure AI systems handling sensitive workforce and HR data meet privacy, residency, and security obligations (GDPR, India's DPDP Act, customer contractual commitments, SOC 2 / ISO controls).
• Partner with Legal, Security, and Privacy on AI governance, vendor and model risk review, and customer-facing AI transparency commitments.
• Build guardrails into the engineering process rather than bolting them on: data-handling standards, prompt and output safety review, tenant isolation, and auditability by default.

You Have What It Takes If You Have…

• 15+ years of software engineering experience, with 7+ years leading engineering teams, including experience managing managers.
• Proven track record of shipping AI/ML or Generative AI systems to production at scale in a product company - not only pilots, POCs, or internal tooling.
• Deep, current technical credibility in AI engineering: LLM application