Job Title

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.