Description

Key Responsibilities

Customer Engagement & Solutioning

Engage with customer stakeholders to understand business challenges and technical requirements.

Translate business problems into scalable technical solutions.

Lead technical discovery workshops, architecture discussions, and solution design sessions.

Solution Development

Build end-to-end prototypes, MVPs, and production-ready applications.

Develop data pipelines, APIs, integrations, dashboards, and AI-powered applications.

Deploy and optimize solutions across cloud environments.

Data & AI Implementation

Implement Data Lakehouse, Analytics, Machine Learning, and GenAI solutions.

Deploy ML and LLM-based applications.

Build RAG, Agentic AI, Knowledge Management, and Copilot solutions.

Technical Leadership

Drive architecture decisions and implementation best practices.

Collaborate with Data Engineers, AI Engineers, Product Teams, and customer IT teams.

Review code, mentor teams, and troubleshoot production issues.

Innovation & Accelerators

Develop reusable frameworks, accelerators, and reference architectures.

Identify opportunities for automation and optimization.

Required Technical Skills

Data Engineering: Python, SQL, Data Modelling, ETL/ELT Pipelines, Data Warehousing, Data Lakehouse Architecture, Spark, and Databricks.

Cloud Platforms: AWS, Azure, or GCP; cloud-native services, containerization, Kubernetes, and Infrastructure as Code.

AI & Generative AI: Machine Learning, LLMs, Agentic AI, RAG Architecture, Prompt Engineering, Vector Databases, and frameworks such as LangChain, LlamaIndex, or Semantic Kernel.

Software Engineering: Python, Java, Scala, or Node.js; REST APIs, Microservices, CI/CD, DevOps, Git, and Agile methodologies.

Preferred Skills

Experience with Snowflake, Databricks, MongoDB, or Red Hat OpenShift.

Domain knowledge in Automotive, Healthcare, Telecom, Manufacturing, Transportation, or Energy.

Experience in MLOps, LLMOps, and enterprise integrations such as SAP, Salesforce, ServiceNow, or Oracle.

Behavioural Competencies

Strong problem-solving and analytical skills.

Excellent communication and stakeholder management.

Ability to balance consulting, engineering, and delivery responsibilities.

Comfortable working in ambiguous, fast-paced environments with a customer-focused mindset.

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, AI, or a related discipline

Key Skills

Education

Bachelor's or Master's degrees