Senior Director, AI Architect

Overview

Senior Director, AI Architect at DISA, leading the AI strategy, enterprise AI platform and in-house AI team across DISA's background screening, drug and alcohol testing, and occupational health operations.

What you'll do

• Define and maintain the enterprise AI strategy and multi-year roadmap, tied to measurable outcomes such as turnaround time, adjudication accuracy, analyst productivity and client retention.
• Serve as the primary AI advisor to business and product stakeholders, translating between technical possibility and commercial consequence.
• Drive AI acceleration across the organization and move teams from curiosity to production use.
• Run structured build-vs-buy-vs-partner evaluations for AI platforms and vendors, owning the recommendation, total cost model and exit path.
• Own AI portfolio investment: prioritization, budget, FinOps discipline on inference and compute spend, and regular value reporting to leadership.
• Architect and deliver the enterprise AI framework covering model access, retrieval, orchestration, evaluation, observability, prompt and context management, and reusable agent patterns.
• Lead the multi-agent orchestration platform from prototype to production-grade, multi-tenant, environment-promoted infrastructure.
• Establish LLMOps and MLOps practice, including CI/CD for models and prompts, regression and eval harnesses, drift and hallucination monitoring, human-in-the-loop feedback capture, incident response and rollback.
• Define reference architectures, integration standards and API contracts, and represent AI work at the Architecture Review Board.
• Set technology direction across Azure AI Foundry / Azure OpenAI and AWS Bedrock, and architect for model and platform portability.
• Benchmark model performance and unit economics across Azure AI Foundry and Bedrock's model catalog and make the platform call per workload on evidence.
• Deliver domain AI solutions in background screening, drug and alcohol testing, and occupational health, plus cross-cutting conversational, agentic, contact center and analytics solutions.
• Own the enterprise AI governance framework, including model inventory and registry, risk tiering, pre-deployment review, bias and fairness testing, explainability requirements, human oversight thresholds and audit evidence.
• Ensure AI systems operate within the regulatory perimeter DISA works in, including FCRA and state screening law, DOT testing regulations, HIPAA, SOC 2 and GDPR, in partnership with Legal, Compliance, Privacy and Security.
• Establish data governance for AI covering lineage, minimization, retention, tenant isolation and controls on the use of consumer and candidate data in training and retrieval.
• Source, shape and prioritize AI use cases and build the business case for each, taking proposals through Technology, Product, Security and Compliance approval.
• Choose the delivery route on merit for each initiative and own vendor selection and management end to end.
• Stay hands-on through delivery: prototype to prove feasibility, review designs and code, and validate model behavior directly.
• Build and lead the AI team at the Mumbai GCC, blending contract and full-time capacity, working with staffing partners, and ensuring knowledge stays with DISA.
• Establish the AI Center of Excellence covering enablement, internal standards, reusable assets and AI literacy programs.
• Coach and grow technical leaders and set the bar for engineering rigor.

What you'll need

• 15+ years in technology, with 6+ years leading AI/ML or data science organizations, including leadership of leaders.
• Proven record of implementing AI solutions at enterprise scale within a product organization, with AI embedded in commercial products serving external customers.
• Understanding of product roadmaps, release cycles, multi-tenancy, SLAs and supporting an AI feature customers pay for.
• Demonstrated delivery of AI systems in production, not pilots, including what was shipped, what it cost, what it returned and what broke.
• Deep hands-on capability in Python and the modern AI stack: LLMs, RAG, agentic architectures, embeddings and vector retrieval, evaluation methodology, classical ML, and document AI/OCR.
• Strong cloud architecture depth across Azure (Azure AI Foundry, Azure OpenAI, AI Search, Document Intelligence, AKS/Container Apps, PostgreSQL, Fabric) and AWS (Bedrock, Knowledge Bases and Agents, Textract, SageMaker).
• Production experience on at least one of Azure or AWS is essential.
• Track record operating in a regulated, audited environment where model decisions affect individuals and must be defensible.
• Proven ability to influence without authority and move an AI agenda through enterprise approval gates.
• Strong vendor and partner management experience, including build-vs-buy decisions defended and lived with.
• Experience building and scaling technical teams in India, ideally within a GCC, global capability center or captive setup.

Nice to have

• Domain exposure to background screening, HR tech, healthcare, clinical or laboratory operations, or another high-volume document and compliance workflow business.
• Experience taking a GCC from delivery execution to product and platform ownership.
• Familiarity with AI governance and model risk management practice in an audited enterprise.
• Advanced degree in Computer Science, Machine Learning, Engineering or a related field.

Details

• Location: Thane, Mumbai.
• Based at the Mumbai GCC.