Director – AIML \ Generative AI

We are seeking a dynamic and
technically strong Director of AI Technology Delivery to lead the end-to-end engineering, deployment, and life cycle management of production-grade AI solutions.
The ideal candidate will possess deep expertise in AI/ML systems, full-stack engineering, database design, and enterprise technology frameworks, and must demonstrate proven experience in driving AI products from prototype to scaled deployment across global business units.

Key Responsibilities:

1. Technology Delivery & Execution

• Own the end-to-end delivery of AI-enabled products, from data ingestion to model deployment and integration into production environments.
• Lead
  full-stack development teams, including front-end , Angular), backend (Python, , Java), APIs (REST/GraphQL), and microservices architecture (Docker, Kubernetes, Kafka).
• Architect, implement, and oversee ML Ops pipelines, ensuring models are versioned, tested, monitored, and deployed securely and reliably.
• Manage high-performance databases (SQL, NoSQL, Graph, Vector DBs) for structured, semi-structured, and unstructured data across AI pipelines.

2. Strategic Technology Oversight

• Define and maintain technical blueprints, solution architecture, and delivery plans for enterprise AI solutions.
• Act as the technical custodian for AI products, aligning with cloud (Azure, AWS, GCP) infrastructure and enterprise security policies.
• Oversee development standards, CI/CD pipelines, observability, and performance tuning for all AI applications.

3. Cross-Functional Collaboration

• Partner with Product Management, AI Research, DevSecOps, UX Design, and Data Engineering teams to deliver AI-based features.
• Ensure alignment between AI experimentation and scalable productionization across business units such as Tax, Audit, ESG, and Advisory.
• Lead technical governance, code reviews, architectural reviews, and compliance against responsible AI frameworks.

4. Team Leadership & Scaling

• Lead a team of senior engineers, AI developers, and data engineers across GDCs and member firms.
• Mentor staff on technical excellence, agile practices, and delivery accountability.
• Drive talent acquisition and technical skill development across the AI delivery squads.

Core Competencies & Skills Required:

Area

Skillset

AI/ML Technologies

Hands-on with Python, PyTorch/TensorFlow, LangChain, LLMs (GPT, Claude, Falcon), Hugging Face, ONNX

Full Stack

, , Django/FastAPI, GraphQL, REST APIs

DevOps/MLOps

Docker, Kubernetes, Airflow, MLflow, GitHub Actions, Azure DevOps, Ray, Terraform

Data & DBs

PostgreSQL, MongoDB, Redis, Neo4j, Milvus/Weaviate/FAISS, Azure Data Lake, Snowflake

Cloud Platforms

Azure AI Studio, AWS SageMaker, Google Vertex AI

Architecture

Event-driven, Microservices, Serverless, API Gateways, Hybrid Edge-to-Cloud Design

Security & Compliance

OAuth2, RBAC, Zero Trust, PII masking, Audit trails, Model explainability (SHAP, LIME)

Delivery Frameworks

Agile, Scrum, SAFE Agile, JIRA, Confluence, GitHub Projects

Qualifications:

• Master's or Ph.D. in Computer Science, Engineering, or related field.
• 14+ years in technology delivery, with 8+ years in AI/ML productization.
• Proven experience delivering AI platforms and digital products at scale.
• Strong leadership in managing distributed engineering teams and AI squads.
• Ability to present and influence at the CXO and Board level on technology vision and delivery health.

KPIs and Success Metrics:

• Delivery of AI products on time, within budget, and with measurable business impact.
• AI solution uptime, model performance (latency, accuracy), and scalability.
• Developer productivity (e.g., PR velocity, commit quality, MTTR).
• AI model governance compliance and audit-readiness.
• Team engagement, retention, and skill advancement across engineering pods