Crystal Peak
Company:
https://www.linkedin.com/company/crystalpeak3181
Seniority: Director
Industries: IT Services and IT Consulting
Job details:
Location: Bengaluru
Job Title: Director/Senior Director AI & Data Analytics
Budget: Upto 1.8 Cr (Fixed + Variable, based on experience and fit)
Employment Type: Full-time
Industry: B2B SaaS Product Company
About the Role:
We are looking for a visionary Head of AI to lead our AI strategy, product innovation, and engineering execution. This is a leadership role for someone who has successfully built and scaled AI products from concept to production while growing high-performing AI organizations from the ground up.
The ideal candidate has experience building AI-first SaaS products, defining long-term AI roadmaps, hiring and mentoring world-class AI talent, and scaling teams from 10 to 100+ members. You will work closely with Product, Engineering, Sales, Customer Success, and Executive Leadership to embed AI into the company's core product offerings.
Key Responsibilities:
AI Strategy & Leadership
- Define and own the company's AI vision, strategy, and execution roadmap.
- Drive AI adoption across all product lines and business functions.
- Identify new AI opportunities aligned with customer needs and business goals.
- Build a culture of innovation, experimentation, and engineering excellence.
AI Product Development
- Lead the design, development, and deployment of AI-powered SaaS products.
- Build intelligent features leveraging:
- Generative AI
- Large Language Models (LLMs)
- AI Agents & Agentic Workflows
- Machine Learning & Deep Learning
- NLP
- Recommendation Systems
- Predictive Analytics
- Computer Vision (where applicable)
- Ensure production-grade AI systems with strong scalability, reliability, security, and observability.
- Own the end-to-end AI product lifecycle-from ideation to production and continuous improvement.
Team Building & Organizational Leadership
- Build, scale, and lead an AI organization from 10 to 100+ professionals, including:
- AI Engineers
- ML Engineers
- Data Scientists
- MLOps Engineers
- Applied Scientists
- Data Engineers
- AI Product Managers
- Hire, mentor, and retain top AI talent.
- Establish engineering standards, performance metrics, and career development frameworks.
- Foster cross-functional collaboration between AI, Product, Engineering, and Business teams.
Technical Leadership
- Architect scalable AI platforms and ML infrastructure.
- Establish best practices around:
- MLOps
- Model lifecycle management
- Model evaluation and monitoring
- Data governance
- Responsible AI
- AI Security
- AI Observability
- Drive adoption of cloud-native AI architectures.
Business & Customer Impact
- Partner with Product and GTM teams to define AI-driven product strategy.
- Translate customer problems into scalable AI solutions.
- Present AI vision and product roadmap to executive leadership, customers, investors, and partners.
- Measure business impact through AI adoption, customer value, and revenue growth.
Required Skills & Experience
Experience
- 15-20+ years of overall experience in Software Engineering, Data Science, and AI.
- 8-10+ years of experience leading AI/ML organizations.
- Proven experience building and launching AI-powered products in a B2B SaaS product company.
- Demonstrated success in scaling AI teams from 10 to 100+ members.
- Strong experience managing multiple engineering managers and senior technical leaders.
- Experience working with global product teams and enterprise customers.
Technical Expertise:
AI & Machine Learning
- Generative AI
- Large Language Models (OpenAI, Anthropic, Gemini, Llama, etc.)
- Agentic AI / Autonomous Agents
- Retrieval-Augmented Generation (RAG)
- Fine-tuning & Prompt Engineering
- NLP
- Deep Learning
- Reinforcement Learning (good to have)
AI Frameworks
- LangChain
- LangGraph
- LlamaIndex
- AutoGen
- CrewAI
- Semantic Kernel
- MCP (Model Context Protocol)
Machine Learning
- TensorFlow
- PyTorch
- Scikit-learn
- XGBoost
Programming
- Python (mandatory)
- SQL
- Java/Scala/Go (good to have)
Cloud & Infrastructure
- Azure
- AWS
- GCP
- Kubernetes
- Docker
MLOps
- MLflow
- Kubeflow
- Airflow
- Weights & Biases
- Vector Databases (Pinecone, Weaviate, Milvus, FAISS)
Data
- Spark
- Kafka
- Snowflake
- Databricks
- BigQuery (good to have)
Leadership Competencies
- Exceptional people leadership and coaching skills.
- Proven experience building organizations from scratch.
- Strategic thinker with strong execution capability.
- Ability to influence C-level executives and cross-functional stakeholders.
- Strong customer-first mindset.
- Excellent communication and presentation skills.
- Comfortable operating in a fast-paced, high-growth environment.
Preferred Qualifications
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Master's or Ph.D. in AI, Machine Learning, Computer Science, or Data Science preferred.
- Publications, patents, or open-source contributions in AI are a plus.
- Experience building AI platforms serving enterprise-scale SaaS customers.
Success Metrics
- Successfully build and scale a high-performing AI organization from 10 to 100+ members.
- Deliver AI-powered product capabilities that drive measurable customer adoption and business growth.
- Improve AI platform scalability, reliability, and deployment velocity.
- Establish a mature AI engineering and MLOps practice.
- Position the company as an AI-first leader in the B2B SaaS market.
Click on Apply to know more.
