AI Tech Lead at T.EN Career Site

, Uttar Pradesh, India -

Full Time

Start Date

Immediate

Expiry Date

01 Jul, 26

Salary

0.0

Posted On

02 Apr, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Azure AI Foundry, Azure OpenAI, Python, Machine Learning, CI/CD Pipelines, Terraform, Agentic RAG, Graph RAG, MLOps, Azure DevOps, System Architecture, Technical Leadership, Data Science, API Management, Software Development, Cloud Computing

Industry

Engineering Services

Description

Be part of the solution at Technip Energies and embark on a one-of-a-kind journey. You will be helping to develop cutting-edge solutions to solve real-world energy problems. We are currently seeking AI Tech Lead, to join our AI & Automation team based in Noida. About us: Technip Energies is a global technology and engineering powerhouse. With leadership positions in LNG, hydrogen, ethylene, sustainable chemistry, and CO2 management, we are contributing to the development of critical markets such as energy, energy derivatives, decarbonization, and circularity. Our complementary business segments, Technology, Products and Services (TPS) and Project Delivery, turn innovation into scalable and industrial reality. Through collaboration and excellence in execution, our 17,000+ employees across 34 countries are fully committed to bridging prosperity with sustainability for a world designed to last. Global Business Services India At Technip Energies, we are continually looking for ways to become more efficient, and ways to improve our quality, customer focus and cost competitiveness. T.EN Global Business Services (TGBS) organization is key to executing this strategy, by standardizing our processes and centralizing our services. Our Vision: A customer focused, cost efficient, innovative, and high performing organization that drives functional excellence. GBS provide streamlined and consistent services to our internal customers in the domain of Finance and Accounting, Human Resources, Business Functional Support, Procurement and Legal. Our services fit our global organization and allow us to focus on business strategy and priorities. GBS also maintains continuous improvement plans to enhance our customer-oriented service culture. About the opportunity we offer: * Leading the technical delivery of AI products and solutions across multiple business domains. * The AI Tech Lead will operate at the intersection of technical architecture, hands-on implementation, and team leadership. This role encompasses: * Architecting and implementing scalable, production-grade AI systems on Azure * Establishing and enforcing technical standards for code quality, security, and performance * Mentoring development teams and fostering a culture of technical excellence * Staying current with emerging AI technologies and driving innovation within the organization Key Responsibilities: 1. Azure Ecosystem Expertise and Architecture * Design and implement complex, scalable AI architectures using Azure services (Azure AI Foundry, Azure OpenAI, Cognitive Services, Azure ML, etc.) * Master-level understanding of Azure Portal, Resource Groups, Azure AI services, and infrastructure provisioning * Lead the design and validation of data architectures in collaboration with Solution Architects * Configure and manage APIM (API Management) for API masking, security, and gateway management * Architect integrations across Azure services, databases (SQL, Cosmos DB, PostgreSQL, etc.), and external systems * Ensure all architecture components are properly configured and integrated within Azure Portal and Azure AI Foundry 2. CI/CD Pipeline and Cybersecurity Implementation * Design, implement, and maintain robust CI/CD pipelines using Azure DevOps, GitHub Actions, or similar tools * Integrate security scanning tools including Snyk (dependency scanning), SonarQube (code quality and security), and other SAST/DAST tools * Establish infrastructure-as-code practices using Terraform, ARM templates, or Bicep * Implement automated testing, deployment strategies (blue-green, canary), and rollback mechanisms * Ensure compliance with security standards, governance policies, and best practices for production deployments 3. Testing Strategy and Quality Assurance Leadership * Lead the development and execution of comprehensive end-to-end (E2E) testing strategies * Define and oversee unit testing frameworks, integration testing, and automated test suites * Implement testing for AI/ML systems including model validation, data quality checks, and performance benchmarking * For chatbot and conversational AI applications, implement RAGAS (RAG Assessment) frameworks for evaluation * Establish quality gates and ensure test coverage meets organizational standards 4. Advanced AI and Machine Learning Implementation * Lead implementation of advanced AI patterns including Agentic RAG (Retrieval-Augmented Generation with autonomous agents) * Architect and deliver Graph RAG solutions for knowledge graph-based retrieval systems * Implement fine-tuning strategies for LLMs, including both supervised fine-tuning and RLHF approaches * Deliver advanced data science projects involving time series analysis, deep learning models, and classical ML algorithms * Stay current with the latest LLM models (GPT-4, Claude, Gemini, Llama, Mistral, etc.), understanding their capabilities, limitations, and optimal use cases * Evaluate and select appropriate models based on performance metrics, cost considerations, and business requirements 5. MLOps and Model Lifecycle Management * Implement MLOps practices for model versioning, tracking, deployment, and monitoring * Establish model governance frameworks ensuring reproducibility, compliance, and auditability * Design and implement monitoring solutions for model performance, drift detection, and retraining triggers * Leverage tools like MLflow, Azure ML, or similar platforms for experiment tracking and model registry * Implement automated retraining pipelines and A/B testing frameworks for model improvements 6. Technical Leadership and Team Development * Lead and mentor development teams (developers, data scientists, ML engineers) in implementing best practices * Conduct code reviews, architectural reviews, and provide technical guidance * Drive technical excellence through knowledge sharing, training sessions, and documentation * Collaborate with cross-functional teams including Product, Design, and Business stakeholders * Foster an agile, collaborative environment that encourages innovation and continuous improvement 7. Requirements Analysis and Project Estimation * Work closely with business stakeholders to understand and document detailed requirements * Challenge vague or incomplete requirements and push stakeholders to provide clarity and specificity * Validate requirements with Solution Architects and ensure feasibility and alignment with technical constraints * Visualize entire delivery workflows, dependencies, and technical architecture for stakeholder communication * Provide accurate effort estimations for development work, considering complexity, risk, and team capacity * Create technical roadmaps and break down work into manageable sprints and milestones 8. Full-Stack Integration and System Design * Design modular, scalable frontend architectures (React, Vue, Angular) with clean separation of concerns * Ensure seamless integration between frontend applications and backend APIs/microservices * Establish API contracts, documentation standards (OpenAPI/Swagger), and versioning strategies * Implement authentication, authorization, and security best practices across the stack * Optimize application performance, including caching strategies, lazy loading, and efficient data fetching 9. Database Architecture and Data Management * Design and optimize database schemas for various database types (SQL Server, PostgreSQL, Cosmos DB, MongoDB) * Implement data pipelines for ETL/ELT processes using Azure Data Factory, Databricks, or similar tools * Ensure data quality, consistency, and governance across systems * Design vector database solutions (Pinecone, Weaviate, Azure AI Search) for RAG implementations * Implement data security measures including encryption at rest and in transit, access controls, and audit logging 10. Innovation and Continuous Learning * Stay updated with the latest developments in AI/ML research, LLM capabilities, and Azure service updates * Research and evaluate emerging technologies, frameworks, and tools for potential adoption * Participate in AI/ML communities, conferences, and forums to stay connected with industry trends * Drive proof-of-concepts (POCs) for innovative solutions and present findings to leadership * Share knowledge through blog posts, internal presentations, and technical documentation About you: * 8-12+ years of experience in software development with at least 3-5 years in technical leadership roles * Deep expertise in Azure ecosystem including Azure Portal, Azure AI Foundry, Azure OpenAI, Cognitive Services, Azure ML, and related services * Proven experience architecting and implementing complex, scalable cloud-based AI systems * Strong proficiency in Python for data science, ML, and backend development * Hands-on experience with CI/CD pipelines (Azure DevOps, GitHub Actions), infrastructure-as-code (Terraform/Bicep) * Expertise with security scanning tools: Snyk, SonarQube, and other SAST/DAST tools * Demonstrated experience leading E2E testing strategies, unit testing, and test automation * Strong understanding of LLMs, transformer architectures, and current state-of-the-art models (GPT-4, Claude, Gemini, Llama, Mistral, etc.) * Hands-on experience with advanced AI patterns: Agentic RAG, Graph RAG, fine-tuning, prompt engineering * Strong knowledge of MLOps practices, model lifecycle management, and monitoring * Experience with RAGAS or similar evaluation frameworks for RAG/chatbot applications * Proficiency in data architecture design and validation * Experience with multiple database technologies (SQL Server, PostgreSQL, Cosmos DB, MongoDB, vector databases) * Understanding of modular frontend development (React/Vue/Angular) and API integration patterns * Strong experience with APIM (API Management), API security, and gateway configurations * Excellent problem-solving skills and ability to work on complex technical challenges * Proven ability to work with ambiguous requirements, push for clarity, and validate technical feasibility * Strong estimation and planning skills for project delivery * Experience leading and mentoring development teams in agile environments * Ability to translate technical concepts for business stakeholders and visualize delivery workflows Your career with us: Working at Technip Energies is an inspiring journey, filled with groundbreaking projects and dynamic collaborations. Surrounded by diverse and talented individuals, you will feel welcomed, respected, and engaged. Enjoy a safe, caring environment where you can spark new ideas, reimagine the future, and lead change. As your career grows, you will benefit from learning opportunities at T.EN University, such as The Future Ready Program, and from the support of your manager through check-in moments like the Mid-Year Development Review, fostering continuous growth and development What’s next? Once receiving your application, our Talent Acquisition professionals will screen and match your profile against the role requirements. We ask for your patience as the team completes the volume of applications with reasonable timeframe. Check your application progress periodically via personal account from created candidate profile during your application. We invite you to get to know more about our company by visiting and follow us on LinkedIn, Instagram, Facebook, X and YouTube for company updates. #LI-AP1

Responsibilities

The AI Tech Lead will architect and implement scalable AI solutions on Azure while leading technical delivery across multiple business domains. This role involves mentoring development teams, establishing technical standards, and driving innovation through advanced AI patterns like Agentic and Graph RAG.