Technical Lead

Job description

To be responsible for managing technology in projects and providing technical guidance / solutions for work completion Key Responsibilities 1. To be responsible for providing technical guidance / solutions ;define, advocate, and implement best practices and coding standards for the team. 2. To develop and guide the team members in enhancing their technical capabilities and increasing productivity 3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations). 4. To prepare and submit status reports for minimizing exposure and risks on the project or closure of escalations. Skill Requirements MUST HAVE GenAI Solution Design & Development • Design and build LLM-powered applications using RAG, embeddings, and vector search architectures • Develop Copilot-based AI assistants and agents for enterprise use cases (automation, Q&A, workflow orchestration) • Engineer end-to-end GenAI pipelines including prompt engineering, context handling, and response orchestration • Build reusable AI components (agents, pipelines, guardrails) to accelerate solution delivery Copilot & AI Agent Development • Develop and customize copilots using Microsoft Copilot Studio / Azure Foundry • Integrate copilots with enterprise systems (ERP, CRM, ServiceNow, APIs) • Design conversational workflows, triggers, and automation actions • Enable enterprise-grade features such as: • Role-based access and identity integration • Knowledge grounding using enterprise data • Responsible AI guardrails (toxicity, hallucination control) Snowflake Cortex / Data AI Engineering • Develop AI-powered applications using Snowflake Cortex AI functions and Snowpark • Implement vector search, semantic models, and AI-driven analytics workflows • Integrate structured and unstructured data pipelines to support AI models • Build self-service AI capabilities on data platforms with governance and cost optimization AI/ML Engineering & MLOps • Build and deploy models using Azure OpenAI, AWS Bedrock, or similar platforms Create scalable pipelines for: • Model deployment • Monitoring and observability • Continuous improvement loops GOOD TO HAVE Implement AI guardrails, evaluation frameworks, and feedback loops for production systems • SDLC Automation with GenAI • Leverage tools like GitHub Copilot for: • Code generation, test automation, debugging, and documentation • Automate SDLC activities using GenAI (requirements → code → testing → deployment) • Enable developer productivity improvements and automation-first engineering • GenAI/LLM solutions (RAG, vector databases, prompt orchestration) • ALign busines priorities with AI outcomes with tangible outcomes and optimizations • Define and curate strategy for Model training, inference, and monitoring, AI OPS ,AI governance elements Responsible AI, fairness, and explain ability • Integrate GenAI into enterprise workflows (chatbots, copilots, knowledge assistants) as appliable and adoptable for relevant business operations architecting solutions across Azure, AWS • Manage AI /Ops and related governance from data collection to retraining and monitoring model drifts Technical Skills: • Hands on knowledge of data models , SQL , data lifecycle management • Strong knowledge of AI/ML algorithms, data structures, and performance optimization. • Proficiency in programming languages such as Python, SQL, and PySpark. • Experience with cloud platforms (AWS, Azure) and big data technologies (Spark, Snowflake),. Other Requirements MUST HAVE GenAI Solution Design & Development • Design and build LLM-powered applications using RAG, embeddings, and vector search architectures • Develop Copilot-based AI assistants and agents for enterprise use cases (automation, Q&A, workflow orchestration) • Engineer end-to-end GenAI pipelines including prompt engineering, context handling, and response orchestration • Build reusable AI components (agents, pipelines, guardrails) to accelerate solution delivery Copilot & AI Agent Development • Develop and customize copilots using Microsoft Copilot Studio / Azure Foundry • Integrate copilots with enterprise systems (ERP, CRM, ServiceNow, APIs) • Design conversational workflows, triggers, and automation actions • Enable enterprise-grade features such as: • Role-based access and identity integration • Knowledge grounding using enterprise data • Responsible AI guardrails (toxicity, hallucination control) Snowflake Cortex / Data AI Engineering • Develop AI-powered applications using Snowflake Cortex AI functions and Snowpark • Implement vector search, semantic models, and AI-driven analytics workflows • Integrate structured and unstructured data pipelines to support AI models • Build self-service AI capabilities on data platforms with governance and cost optimization AI/ML Engineering & MLOps • Build and deploy models using Azure OpenAI, AWS Bedrock, or similar platforms Create scalable pipelines for: • Model deployment • Monitoring and observability • Continuous improvement loops GOOD TO HAVE Implement AI guardrails, evaluation frameworks, and feedback loops for production systems • SDLC Automation with GenAI • Leverage tools like GitHub Copilot for: • Code generation, test automation, debugging, and documentation • Automate SDLC activities using GenAI (requirements → code → testing → deployment) • Enable developer productivity improvements and automation-first engineering • GenAI/LLM solutions (RAG, vector databases, prompt orchestration) • ALign busines priorities with AI outcomes with tangible outcomes and optimizations • Define and curate strategy for Model training, inference, and monitoring, AI OPS ,AI governance elements Responsible AI, fairness, and explain ability • Integrate GenAI into enterprise workflows (chatbots, copilots, knowledge assistants) as appliable and adoptable for relevant business operations architecting solutions across Azure, AWS • Manage AI /Ops and related governance from data collection to retraining and monitoring model drifts Technical Skills: • Hands on knowledge of data models , SQL , data lifecycle management • Strong knowledge of AI/ML algorithms, data structures, and performance optimization. • Proficiency in programming languages such as Python, SQL, and PySpark. • Experience with cloud platforms (AWS, Azure) and big data technologies (Spark, Snowflake),. Apply now Information at a Glance Why HCLTech? At HCLTech, you'll supercharge your potential. You'll find your career. And you'll find your spark. All at a place that knows that helping its customers stay on top starts by putting its people first. HCLTech is a global technology company, home to more than 230,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending September 2026 totaled $14.8 billion. • Disclaimer • Privacy Statement • Terms of use • Sitemap • Raise a Grievance • We use cookies on our site. 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