Director - AI Technology Delivery

Summary :

We are seeking a dynamic and technically strong Director of AI Technology Delivery to lead the end-to-end engineering, deployment, and lifecycle 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 :

- Lead full-stack development teams, including frontend (React.js, Angular), backend (Python, Node.js, 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 :

- 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 :

- 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 :

- 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 :

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

- Full Stack : React.js/Next.js, Node.js/Express, 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 :

- 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 :

- 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