We are a leading provider of telecom analytics solutions

Role : Senior Director - AI/ML & GenAI\

About the Job :

We are building a high-impact engineering team to deliver AI/ML and Generative AI capabilities for telecom-grade platforms (roaming, security, analytics, customer experience). The Sr. Director will lead engineering strategy, architecture, and delivery for GenAI services and platform components. This role blends hands-on technical depth with strategic leadership across model training, serving, evaluation, infrastructure, and security-customized for the demands of telecom data and performance.

Roles & Responsibility :

1. Engineering Strategy & Technical Vision:

- Roadmap : Define the engineering roadmap for GenAI platform capabilities-training pipelines, inference layers, and domain-specific services.

- Goals : Establish clear non-functional goals (e.g., SLOs, quality metrics, performance KPIs) and drive alignment across engineering and product.

2. GenAI Model Lifecycle Management:

- LLM Workflows : Oversee pretraining, fine-tuning (SFT), LoRA/PEFT adaptation, and deployment of domain-specific LLMs.

- Guardrails : Build safety filters, hallucination checks, and prompt validation to ensure GenAI output quality and reliability.

3. AI Infrastructure & MLOps:

- Pipelines : Lead model CI/CD, reproducible pipelines, deployment frameworks, and GPU capacity planning.

- Reliability : Partner with SREs to establish observability standards and incident-handling protocols for AI/LLM systems.

4. Platform & Data Architecture:

- Services : Architect scalable services supporting vector search, retrieval-augmented generation (RAG), embedding storage, and model evaluation.

- Telco Data : Lead ingestion and integration strategies for telecom-centric data (CDRs, logs, network KPIs).

5. Release Management & Quality Assurance:

- Validation : Own model validation strategy-unit/perf tests, dataset quality checks, drift detection, and safety evaluations.

- QE Partnership : Collaborate with QE for automation and pre-release validations.

6. Privacy, Compliance & Responsible AI:

- Controls : Enforce data minimization, encryption, access controls, and alignment with GDPR/DPDP via engineering practices.

- Responsible AI : Guide auditability and transparency in the platform architecture.

7. Team Building & Technical Leadership:

- Hiring : Recruit and develop AI/ML engineers, MLOps specialists, and platform architects.

- Culture : Foster performance engineering, clean architecture, and collaboration.

8. Cross-functional Execution

- Partnerships : Interface with Product, Security, Platform, and QE teams to ensure scalable, reliable GenAI delivery.

- Ownership : Maintain architectural and code-level ownership while influencing cross-org execution.

Desired Profile :

- Telecom domain exposure (xDRs, OSS/BSS, network analytics, firewall/security).

- Experience with streaming/OLAP systems (Kafka, ClickHouse) and vector DBs (pgvector, FAISS).

- Strong grasp of model evaluation, prompt testing, and inference efficiency techniques.

Technical Skills :

- AI Systems Architecture : End-to-end design of scalable, performant GenAI systems.

- Operational Readiness : SLO compliance, uptime, monitoring, and incident response.

- Hands-on Technical Leadership : Deep reviews, mentoring, and a high quality bar.

- Execution Focus : Outcome ownership and iterative delivery of engineering plans.

- Strategic Vision : Prioritize investments and platform evolution roadmap.

Tech Stack Overview :

- LLM/GenAI : PyTorch, HuggingFace, Transformers, LoRA/PEFT

- Serving : vLLM, Triton, KServe, REST/gRPC

- Data : Kafka, ClickHouse, pgvector, Spark/Flink

- MLOps : MLflow, GitHub Actions, Argo, Helm

- Infra & Security : Kubernetes, OpenShift, Prometheus, etc.

Work Experience :

- 12+ years in software/AI engineering; 5+ years leading ML/GenAI engineering teams.

Educational Qualification :

- Master's/Ph.D. in CS/EE/Math (or related discipline) with strong grounding in ML, GenAI, and distributed systems.

Location : Bangalore