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 / PEFTServing : vLLM, Triton, KServe, REST / gRPCData : Kafka, ClickHouse, pgvector, Spark / FlinkMLOps : MLflow, GitHub Actions, Argo, HelmInfra & 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
(ref : hirist.tech)