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Job Description: Generative AI Technical Lead Developer: AI + ML+NLP with Generative AI Total Years of Experience: 9-12 Years Location: Bengaluru / Gurugram Position Overview: We are seeking an experienced and dynamic Lead Developer with a strong background in Machine Learning (ML), Artificial Intelligence (AI) and Generative AI to join our team. The ideal candidate will have 9-12 years of hands-on experience in analyzing data, building advanced analytics models, and leveraging cutting-edge AI and Generative AI technologies to derive actionable insights. This role requires a combination of deep technical expertise, strong analytical capabilities, and a proven ability to work in a collaborative and innovative environment. Responsibilities: Architecture Design: Design and implement scalable, secure, and high-performance architectures for Generative AI applications. Integrate Generative AI models into existing platforms, ensuring compatibility and performance optimization. Model Development and Deployment: Fine-tune pre-trained generative models for domain-specific use cases. Data Collection, Sanitization and Data Preparation strategy for Model fine tuning. Well versed with machine learning algorithms like Supervised, unsupervised and Reinforcement learnings, Deep learning. Well versed with ML models like Linear regression, Decision trees, Gradient boosting, Random Forest and K-means etc. Evaluate, select, and deploy appropriate Generative AI frameworks (e.g., PyTorch, TensorFlow, Crew AI, Autogen, Langraph, Agentic code, Agent flow). Innovation and Strategy: Stay up to date with the latest advancements in Generative AI and recommend innovative applications to solve complex business problems. Define and execute the AI strategy roadmap, identifying key opportunities for AI transformation. Good exposure to Agentic Design patterns Collaboration and Leadership: Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders. Mentor and guide team members on AI/ML best practices and architectural decisions. Should be able to lead a team of data scientists, GenAI engineers and Software Developers. Performance Optimization: Monitor the performance of deployed AI models and systems, ensuring robustness and accuracy. Optimize computational costs and infrastructure utilization for large-scale deployments. Ethical and Responsible AI: Ensure compliance with ethical AI practices, data privacy regulations, and governance frameworks. Implement safeguards to mitigate bias, misuse, and unintended consequences of Generative AI. Required Skills: Advanced programming skills in Python and fluency in data processing frameworks like Apache Spark. Experience with machine learning, artificial Intelligence frameworks models and libraries (TensorFlow, PyTorch, Scikit-learn, etc.). Should have strong knowledge on LLMs foundational model (OpenAI GPT4o, O1, Claude, Gemini etc), while need to have strong knowledge on opensource Model’s like Llama 3.2, Phi etc. Proven track record with event-driven architectures and real-time data processing systems. Familiarity with Azure DevOps and other LLMOps tools for operationalizing AI workflows. Deep experience with Azure OpenAI Service and vector DBs, including API integrations, prompt engineering, and model fine-tuning. Or equivalent tech in AWS/GCP. Knowledge of containerization technologies such as Kubernetes and Docker. Comprehensive understanding of data lakes and strategies for data management. Expertise in LLM frameworks including Langchain, Llama Index, and Semantic Kernel. Proficiency in cloud computing platforms such as Azure or AWS. Exceptional leadership, problem-solving, and analytical abilities. Superior communication and collaboration skills, with experience managing high-performing teams. Ability to operate effectively in a dynamic, fast-paced environment. • Nice to Have Skills: Experience with additional technologies such as Datadog, and Splunk. Programming languages like C#, R, Scala Possession of relevant solution architecture certificates and continuous professional development in data engineering and Gen AI. Professional and Educational Background: BE / B.Tech / MCA / M.Sc / M.E / M.Tech
