Director, Software Engineering & Development

Ascensus•Boston, MA

1d•$170,000 - $220,000

About The Position

Ascensus is the leading independent technology and service platform powering savings plans across America, providing products and expertise that help nearly 16 million people save for a better today and tomorrow. Position Summary As a Software Engineering Manager, Enterprise AI Platform, you will lead a team responsible for building, operating, and continuously improving production-grade AI-enabled software. This role manages a cross-functional engineering team that may include: Software Engineers SDETs DevOps Engineers Support Engineers This is a hands-on engineering leadership role for someone who has strong software engineering experience, cares deeply about people development, and can help teams deliver practical AI-powered solutions with speed, quality, and discipline. While this is a management role, the person in this position is expected to stay close to the codebase and technical workflow. When the situation calls for it, they may contribute directly to implementation, debugging, automation, technical spikes, or code reviews to help the team move faster, remove blockers, or solve critical problems. You will be responsible for: Growing and developing engineering talent Creating a high-performance team culture Supporting delivery of enterprise AI platform capabilities Improving engineering practices across software development, testing, DevOps, support, and operations Partnering with product, architecture, AI, business, and technology leaders Helping the team move quickly while maintaining quality, security, reliability, and maintainability Occasionally contributing hands-on to implementation, debugging, automation, technical spikes, or code reviews when the situation calls for it This role is ideal for an emerging engineering leader who has already demonstrated strong technical leadership and people leadership potential, and who is looking to continue growing and evolving their career. We are looking for someone who can lead through influence, coach engineers effectively, improve team execution, and help build the operating model for modern AI-enabled software delivery. What We’re Looking For We are looking for a manager who can balance people leadership, technical judgment, and delivery execution. The ideal candidate is someone who: Has a strong software engineering background Understands how modern software teams build, test, deploy, and operate production systems Can coach software engineers, SDETs, DevOps engineers, and support engineers Stays technically engaged with the team’s codebase, architecture, development workflow, and operational tooling Knows when to guide, when to delegate, and when to contribute hands-on to help the team move forward Knows how to create clarity in ambiguous environments Can translate business and platform goals into team execution Has strong instincts around quality, automation, observability, reliability, and supportability Is comfortable working in a fast-moving AI environment Can partner well with product owners, architects, data scientists, business stakeholders, and senior leaders Wants to grow into broader engineering leadership responsibility over time This is a software engineering management role focused on building and growing the team that delivers and operates the Enterprise AI Platform.

Requirements

5+ years of professional software engineering or related technical experience.
2+ years of technical leadership, team leadership, people leadership, or engineering management experience.
Experience leading, coaching, or mentoring software engineers or related technical team members.
Ability and willingness to stay technically engaged with the team’s codebase, architecture, development workflow, and operational tooling, including occasional hands-on contribution when needed.
Strong understanding of modern software engineering practices, including: Clean code, Source control, Unit testing, CI/CD, Design patterns, Refactoring, Maintainability, Production support
Experience working with software delivery teams that include roles such as: Software Engineers, SDETs, DevOps Engineers, Support Engineers, Quality Engineers
Experience supporting production software systems, including troubleshooting, incident response, root-cause analysis, or operational improvement.
Strong understanding of Agile delivery practices and modern engineering team workflows.
Ability to develop associates through coaching, feedback, goal setting, performance conversations, and career development planning.
Ability to create a high-performance team environment built on ownership, accountability, trust, and continuous improvement.
Strong communication skills with technical and non-technical audiences.
Strong problem-solving, prioritization, and decision-making skills.
Ability to partner with product, architecture, operations, support, and business teams to drive successful outcomes.
Experience participating in hiring, interviewing, candidate evaluation, or team growth activities.
Bachelor’s degree in Computer Science, Computer Information Systems, Business Information Systems, a related technical field, or equivalent practical experience.

Nice To Haves

Managing or leading teams that build enterprise platforms, internal developer platforms, AI platforms, or shared services
Experience with AI-enabled applications, LLM-powered systems, RAG, chatbots, agent workflows, or AI-assisted engineering practices
Familiarity with Azure, Azure AI Foundry, Azure DevOps, or related Microsoft cloud and engineering tools
Experience with engineering teams using AI-powered development tools such as Cursor, Claude Code, or similar platforms
Experience leading teams that use automated testing, SDET practices, Playwright, Python-based test automation, or end-to-end testing
Experience with DevOps practices, CI/CD pipelines, release automation, infrastructure automation, or cloud operations
Experience with observability tools such as New Relic, Langfuse, OpenTelemetry, Azure Log Analytics, or similar platforms
Experience managing geographically distributed teams
Experience improving production support models, incident management, operational readiness, or service reliability
Experience working with enterprise systems such as Salesforce, internal platforms, APIs, workflow systems, or service-oriented architectures
Experience leading teams through ambiguity, rapid change, or emerging technology adoption
Experience building succession plans, development plans, hiring strategies, or team capability roadmaps
Interest in continuing to grow leadership responsibility

Responsibilities

Growing and developing engineering talent
Creating a high-performance team culture
Supporting delivery of enterprise AI platform capabilities
Improving engineering practices across software development, testing, DevOps, support, and operations
Partnering with product, architecture, AI, business, and technology leaders
Helping the team move quickly while maintaining quality, security, reliability, and maintainability
Occasionally contributing hands-on to implementation, debugging, automation, technical spikes, or code reviews when the situation calls for it
Lead through influence, coach engineers effectively, improve team execution, and help build the operating model for modern AI-enabled software delivery.
Build a team that delivers high-quality software consistently.
Develop engineers, SDETs, DevOps engineers, and support engineers into stronger technical contributors.
Create a culture of ownership, accountability, speed, and quality.
Stay technically close enough to guide decisions, unblock the team, and occasionally contribute hands-on without becoming a bottleneck or displacing team ownership.
Help the team use AI-assisted development tools without lowering engineering standards.
Improve how the team builds, tests, deploys, monitors, and supports software.
Partner effectively with product owners, architects, data scientists, business stakeholders, and senior leaders.
Create clarity when priorities are ambiguous or changing.
Raise the quality of engineering practices across the team.
Identify performance gaps early and address them directly and constructively.
Hire strong talent and help retain high-performing associates.
Help the team connect day-to-day execution to broader Enterprise AI Platform goals.
Grow your own leadership scope, judgment, and organizational influence over time.