Lead Software Engineer -26260

Job description

Why YOU want this position: Enverus is the leading energy SaaS company, delivering advanced technical insights and predictive/prescriptive analytics that empower customers to make profitable decisions. Our innovative technologies drive production and investment strategies, enhance energy and commodity trading and risk management, and reduce costs through automation of critical business functions. Enverus is a strategic partner to over 6,000 customers in 50 countries. We are seeking a Software Tech Lead to spearhead the development of our groundbreaking software solutions. If you are passionate about leading a team while being hands-on with coding and thrive in fast-paced projects with North American teams, you’ll find a rewarding experience with us. As a Software Tech Lead, you will utilize cutting-edge techniques to build APIs and complex data pipelines, taking end-to-end ownership of the features you develop. We seek a developer with natural curiosity, full-stack experience, and a commitment to continuous learning and adaptation. The Team: You will join our software engineering team at the forefront of innovation in the energy industry. Our highly collaborative and agile group is dedicated to prototyping and leveraging cutting-edge technologies to develop new products and solutions. Join us and help pioneer Enverus’s mission to drive the future of energy. What you will do: Lead and mentor a small team of engineers, providing technical direction, code review, and day-to-day guidance while remaining an active, hands-on contributor. Collaborate across multiple concurrent projects and workstreams, balancing your own coding time with team leadership and cross-team coordination. Develop robust and scalable backend solutions, integrating them with various AWS services. Design, build, and maintain data processing pipelines leveraging various AWS services. Design and build AI-powered and agentic features — e.g., LLM-based services, retrieval-augmented generation (RAG), and multi-agent workflows — as part of our product roadmap. Evaluate and apply Gen-AI tooling (LLM APIs, vector databases, orchestration frameworks) to improve product capability and engineering velocity. Collaborate with cross-functional teams to understand requirements and translate them into technical solutions, ensuring alignment with best practices and AWS architecture principles. Write maintainable code in a professional agile software engineering environment (source control, shortened release cycles, continuous integration/deployment, etc.). Optimize application performance and scalability by fine-tuning AWS resources and leveraging advanced techniques. Drive technical decision-making, including architecture reviews, technology evaluations, and trade-off discussions with peers and leadership. What you should have: A Bachelor's or Master's degree in Computer Science , Engineering, or a related field. 8+ years of experience in software development, including at least 2–3 years leading or mentoring engineers (formally or informally). Ability to work from 3 PM IST Demonstrated experience managing or guiding a small team while staying hands-on with coding — this is not a purely people-management role. Deep, hands-on expertise numerous programming languages, relational databases, source control, and CI/CD. Strong understanding of software architecture principles, design patterns, and best practices, with the judgment to make and defend technical trade-offs. Experience with cloud platforms such as AWS. Practical experience with AI/LLM and agentic engineering — e.g., building with LLM APIs, prompt/context engineering, RAG pipelines, vector stores, or agent orchestration frameworks (such as LangGraph, AutoGen, or similar). Proficiency in Data Structures and Algorithms, with strong mathematical problem-solving abilities. Familiarity with front-end and back-end technologies and frameworks. Proven ability to work across multiple projects simultaneously, prioritizing effectively under shifting demands. Excellent leadership, team management, and mentoring skills. Strong problem-solving and analytical skills. Effective communication and interpersonal skills, comfortable collaborating with North American teams. Ability to prioritize, raise issues, and resolve challenging problems promptly to meet business deadlines. Self-motivated, task-oriented personality with a strong work ethic and desire to learn. Nice to have: Hands-on experience fine-tuning or evaluating LLMs, or building production agentic systems. Experience with MCP (Model Context Protocol) or similar tool-calling/agent standards. Exposure to observability tooling for AI systems (e.g., Langfuse, Phoenix) or LLMOps practices. Prior experience in the energy, SaaS, or data-analytics domain.