Data & Ai Practice Head

Key ResponsibilitiesStrategic Leadership- Define and execute the Data & AI practice strategy across data engineering, analytics, AI/ML, GenAI, MLOps, and data governance.- Track industry trends, emerging technologies, and competitive landscapes to strengthen Focaloid’s positioning.- Expand the service portfolio with new Data & AI offerings aligned to evolving client needs and market opportunities.Practice & Capability Building- Build, mentor, and scale a multidisciplinary team of data engineers, AI/ML experts, data scientists, and analysts.- Establish competency development frameworks and drive continuous upskilling in modern data stacks, cloud platforms, and AI technologies.- Oversee workforce planning, hiring, and resource allocation to meet delivery and growth objectives.Client Engagement & Solutioning- Partner with sales and presales teams to craft compelling Data & AI solutions, proposals, and presentations.- Engage with C‑suite stakeholders to understand business challenges and design tailored, outcome‑driven solutions.- Build long‑term client relationships and expand existing accounts through consultative engagement.Delivery Excellence- Provide architectural oversight for large‑scale data platforms, AI/ML solutions, and cloud‑native data ecosystems.- Ensure timely, high‑quality delivery of projects with strong alignment to client expectations and business outcomes.- Establish and enforce best practices for data quality, security, governance, and compliance (GDPR, HIPAA, etc.).Innovation & Thought Leadership- Drive R&D initiatives in emerging Data & AI technologies, including GenAI, LLMOps, real‑time analytics, and automation.- Pilot innovative solutions and accelerators to strengthen Focaloid’s competitive edge.- Represent Focaloid in conferences, industry forums, and thought leadership platforms through whitepapers, talks, and expert contributions.Business Growth- Identify new business opportunities and drive revenue growth across Data & AI service lines.- Build strategic partnerships with cloud providers, AI platform vendors, and technology partners.- Collaborate with marketing to strengthen employer branding and market visibility for the Data & AI practice.Technical Skills & ExperienceConventional Data & Machine Learning- Data engineering: SQL, ETL, data pipelines, data warehousing- Feature engineering, model development, hyperparameter optimization- Programming: Python, R, SQL, PySpark, Scala- ML frameworks: TensorFlow, PyTorch, Scikit‑learn, XGBoost, LightGBM- Applied ML: time‑series forecasting, document classification, clustering, anomaly detectionGenAI & Large Language Models- Retrieval‑Augmented Generation (RAG) architectures- Vector databases: Qdrant, Pinecone, FAISS, Chroma- Multi‑agent frameworks: LangGraph, CrewAI, AutoGen, Haystack Agents- Prompt engineering, fine‑tuning, LoRA, embeddings- Document intelligence: OCR, structured/unstructured extraction- Tool use, function calling, and agentic workflowsCloud & Data Platforms- Azure: Azure AI, Azure OpenAI, Data Factory, Synapse, Databricks- AWS: Bedrock, S3, EC2, RDS, Glue, Athena, SageMaker- GCP: Vertex AI, BigQuery, Dataflow, Pub/Sub- Snowflake, Redshift, PostgreSQL, KafkaMLOps & Productionization- CI/CD for ML and GenAI pipelines- Model deployment: Docker, Kubernetes- Monitoring: drift detection, accuracy tracking, hallucination checks- API orchestration, microservices, event‑driven architectureRequirements- Bachelor’s degree in Engineering or related field with 15+ years of experience delivering enterprise data and AI solutions using Agile methodologies.- Proven experience as a Practice Head, Delivery Head, or Data Transformation Leader building Data & AI capabilities.- Strong background in leading large‑scale data engineering, analytics, AI/ML, and cloud transformation programs.- Experience working in a matrix environment with global sales, delivery, and marketing teams.- Demonstrated success in presales, proposal creation, solutioning, and business development.- Deep expertise in modern data technologies, cloud platforms (AWS/Azure/GCP), AI/ML frameworks, and GenAI ecosystems.- Excellent leadership skills with the ability to influence, inspire, and drive high‑performance teams.- Strong communication and presentation skills, including experience engaging with C‑suite stakeholders.- Resilient, resourceful, and comfortable working in fast‑paced, multicultural, multi‑location environments.- Proven ability to build trusted relationships with clients and internal stakeholders.