AI-Native Software Engineering Lead / Agentic Development Expert
Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on Oct 20, 2026.
We are looking for an experienced, hands-on AI-Native Software Engineering Lead to drive the transformation of software development practices within a complex enterprise banking environment.
The objective is to fundamentally modernize the Product Development Lifecycle (PDLC) and Software Development Lifecycle (SDLC) by introducing AI-powered coding agents, autonomous engineering workflows, and AI-first development methodologies.
This role is not focused on building traditional AI applications or chatbots. Instead, you will work directly with engineering teams to demonstrate how AI agents can automate substantial parts of the software development process, from requirements analysis to implementation, testing, and deployment.
Drive the adoption of AI-native software engineering practices within established enterprise development teams.
Design, implement, and optimize agentic development workflows using AI coding agents and LLM-powered automation.
Automate engineering activities, including requirements analysis, codebase exploration, solution design, code generation, testing, code reviews, and deployment preparation.
Integrate AI-powered development tools, particularly GitHub Copilot and autonomous coding agents, into existing engineering environments.
Transform traditional SDLC processes into AI-first workflows with clearly defined human oversight and quality gates.
Develop practical proofs of concept and implement AI-driven automation within existing enterprise applications and complex codebases.
Establish governance mechanisms covering AI-generated code, validation, traceability, approval workflows, and accountability.
Collaborate closely with software engineers, architects, DevOps specialists, and platform teams.
Mentor and coach development teams in adopting AI-assisted and increasingly autonomous engineering practices.
Conduct technical workshops, demonstrations, and knowledge-sharing sessions to accelerate AI adoption.
Extensive professional experience in software engineering, including designing, developing, testing, and maintaining enterprise applications.
Proven hands-on experience with AI-powered software development tools and coding agents, preferably GitHub Copilot.
Practical experience with LLMs, Generative AI, tool/function calling, RAG, structured extraction, and agentic workflows.
Demonstrated experience implementing AI-powered automation or agentic workflows within existing large-scale software projects, rather than exclusively standalone prototypes.
Strong understanding of the complete SDLC and PDLC, including requirements engineering, software architecture, development, testing, deployment, and maintenance.
Experience working with complex enterprise codebases, established architectures, and mature engineering processes.
Solid knowledge of DevOps practices, CI/CD pipelines, and engineering automation.
Ability to independently develop proofs of concept and translate experimental approaches into practical engineering solutions.
Experience mentoring software engineers and introducing new development tools, practices, and methodologies.
Excellent communication, consulting, and stakeholder management skills.
A pragmatic, hands-on mindset with the ability to work independently and collaboratively in dynamic environments.