Team Lead

Job Description Position Overview We are seeking an exceptional AI Expert and Team Lead to spearhead our AI Center of Excellence at Esyasoft, Mangalore. This role combines deep technical expertise in AI/ML with strong leadership capabilities to guide high-potential graduate engineers from premier institutions in developing cutting-edge AI solutions for the utilities sector. As a pioneer in our AI CoE, you will architect and implement AI agents and agentic workflows using open-source models, progressing toward fine-tuning and ultimately developing utility-specific Large Language Models (LLMs). This is a unique opportunity to shape the future of AI applications in utilities while building and mentoring an elite engineering team. Key Responsibilities Phase 1: AI Agent & Agentic Workflow Implementation Lead the design and implementation of AI agents and agentic workflows for utilities use cases Architect scalable solutions using open-source LLMs (e.g.Llama, Mistral, Qwen, etc.) and frameworks (e.g.LangChain, LlamaIndex, Dify, AutoGen) Establish best practices for prompt engineering, RAG (Retrieval-Augmented Generation), and multi-agent orchestration Guide graduate trainees in hands-on implementation, code reviews, and technical problem-solving Collaborate with utilities domain experts to translate business requirements into technical solutions Phase 2: LLM Fine-tuning & Optimization Lead fine-tuning initiatives to adapt open-source LLMs for utilities-specific terminology, regulations, and workflows Design and implement RLHF (Reinforcement Learning from Human Feedback) pipelines with domain expert feedback Optimize model performance through quantization, pruning, and efficient deployment strategies Build evaluation frameworks to measure model performance on utilities-specific benchmarks Mentor team members in advanced ML techniques including parameter-efficient fine-tuning (e.g. LoRA, QLoRA) Phase 3: Utility-Focused LLM Development Contribute to the development of a proprietary LLM trained on utilities-focused datasets Curate and prepare training datasets from utilities documentation, technical manuals, regulatory texts, and operational data Design training pipelines for pre-training and continued pre-training on domain-specific corpora Establish data governance and ensure compliance with data privacy regulations Publish research findings and represent Esyasoft at industry conferences and forums Leadership & Team Development Lead and mentor a team of 8-15 graduate trainees from premier institutes, fostering their technical growth and career development Create a culture of innovation with regular knowledge-sharing sessions, paper reading groups, and hackathons Conduct technical interviews and participate in hiring decisions for AI CoE expansion Manage project timelines and deliverables, ensuring alignment with business objectives Collaborate cross-functionally with product, engineering, and business teams Required Qualifications Education Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or related field Premier institution background (IITs, IISc, top global universities) strongly preferred Technical Expertise 5-8 years of hands-on experience in AI/ML with demonstrable expertise in: Large Language Models (LLMs) and Transformer architectures Fine-tuning techniques (full fine-tuning, LoRA, QLoRA, PEFT) Agentic AI frameworks (LangChain, LlamaIndex, AutoGen, CrewAI) Open-source LLM deployment (vLLM, TGI, Ollama, LM Studio) RAG (Retrieval-Augmented Generation) systems and vector databases Strong programming skills in Python with proficiency in: PyTorch, TensorFlow, or JAX HuggingFace Transformers, Accelerate, PEFT FastAPI, Flask for API development Docker, Kubernetes for containerization Experience with MLOps including: Experiment tracking (MLflow, Weights & Biases) Model versioning and deployment pipelines Monitoring and observability tools Research & Product Development Published research in top-tier conferences (NeurIPS, ICML, ACL, EMNLP) or high-impact journals (preferred) Track record of shipping ML products from prototype to production Experience with open-source contributions to AI/ML projects Strong understanding of LLM evaluation methodologies and benchmarks Leadership & Soft Skills Proven ability to lead and mentor high-potential engineers Excellent communication skills with the ability to explain complex technical concepts to diverse audiences Strategic thinking with both research-oriented and product-oriented mindset Strong problem-solving abilities and capacity to work on ambiguous, open-ended challenges Collaborative approach with experience working in cross-functional teams   Preferred Qualifications Domain expertise in utilities, energy, or related industries Experience with domain-specific LLM development or fine-tuning for vertical industries Knowledge of utilities operations including grid management, demand response, regulatory frameworks Familiarity with tools like Dify, n8n, or other low-code AI platforms Experience with distributed training frameworks (DeepSpeed, Megatron-LM, FSDP) Track record of building AI teams from the ground up Active participation in AI research communities and open-source ecosystems What We Offer Leadership opportunity to build and shape the AI CoE from the foundation Cutting-edge projects at the intersection of AI and utilities transformation Talented team of engineers from premier institutions Research freedom to explore novel approaches and publish findings Competitive compensation including base salary, performance bonuses, and equity options Professional development budget for conferences, courses, and certifications State-of-the-art infrastructure including GPU clusters for model training Flexible work environment with a focus on outcomes over hours Collaborative culture that values innovation, learning, and impact Requirements 3-8 years of experience as a Linux System Administrator. Strong knowledge of Linux server distributions (RHEL, CentOS, Ubuntu). Good understanding of networking, DNS, DHCP, VPN, firewalls. Experience with scripting (Bash, Python, Perl) for automation. Hands-on experience with virtualization technologies (VMware, KVM, Hyper-V). (Good to have) Familiarity with cloud platforms (AWS, Azure, or GCP). Working knowledge of monitoring tools (Nagios, Zabbix, Prometheus, Grafana). Experience with version control (Git). Strong troubleshooting and problem-solving skills. Good understanding of IT security principles. Excellent documentation and communication skills.