Senior Manager, Software Engineer

ICF•Reston, VA

6d•$131,256 - $223,134•Remote

About The Position

ICF is seeking a Senior Manager, Software Engineer to lead the engineering team responsible for Sightline ADAPT, a client-facing analytics and decision-support platform for the utility and energy industries. The role directly manages a growing team of software and data engineers and owns the engineering roadmap, major technical decisions, cloud and production practices, and standards for secure, reliable, scalable products. The Senior Manager combines people leadership with technical judgment, product thinking, and an AI-first mindset. The role guides Sightline ADAPT from analytical workflows and rapidly developed prototypes toward maintainable, supportable products, partnering with product and business leaders to align technical investments with user needs, client commitments, and business outcomes. Sightline ADAPT is evolving from project-based analytical capabilities into a reusable platform that integrates customer, building, energy-usage, program, distributed-energy-resource, and grid data to support utility planning and implementation decisions. The role establishes engineering practices, delivery models, technical direction, and governance to turn prototypes and analytical methods into maintainable applications and shared platform capabilities. The position is remote within the United States.

Requirements

Bachelor’s degree in a relevant technical field.
At least 5 years of progressive software engineering experience, including leading complex engineering or product initiatives.
Prior people management experience directly leading software or data engineers, including coaching, performance management, hiring, and team development.
Experience leading data-intensive, client-facing software products from development through production, scaling, and support in cloud environments.
Strong experience with Python, SQL, APIs, data engineering, front-end technologies, cloud services, CI/CD, and modern software development practices.
Experience setting technical roadmaps, leading cross-functional engineering initiatives, and applying AI-assisted development tools or AI-enabled capabilities.
Strong ability to communicate technical decisions, priorities, risks, and tradeoffs to technical, client, and executive audiences.
Authorization to work in the United States.

Nice To Haves

Master’s degree in computer science, software engineering, data science, information systems, or a related field.
Experience with Microsoft Azure, Azure DevOps, Databricks, Apache Spark, and Docker.
Experience developing data-intensive SaaS platforms, analytical products, or configurable multi-client applications.
Experience with React, Next.js, FastAPI, .NET, or comparable modern full-stack application frameworks.
Experience operationalizing machine-learning, optimization, digital-twin, generative-AI, or agentic capabilities, including evaluation and monitoring.
Experience navigating enterprise architecture, cybersecurity, privacy, software-governance, and production-readiness reviews.
Experience with utility-sector data and analytical use cases, including customer, AMI, programs, DERs, forecasting, or distribution planning.
Familiarity with utility planning and operational technologies such as OpenDSS, CYME, Synergi, DERMS, or ADMS.
Experience supporting technical sales, proposals, demonstrations, client discovery, and modernization of analytical codebases or prototypes.

Responsibilities

Directly manage an initial team of three engineers, including performance management, coaching, career development, hiring, onboarding, and future team growth.
Set clear expectations, roles, decision rights, and development responsibilities, and foster a collaborative, accountable, and inclusive engineering culture.
Plan team capacity, assign work, remove delivery barriers, and develop engineers’ technical and leadership capabilities.
Provide engineering leadership across product, data science, analytics, consulting, infrastructure, security, and client-delivery teams.
Partner with product, consulting, and client leaders to translate utility use cases into prioritized capabilities, technical requirements, epics, user stories, acceptance criteria, release plans, and measurable outcomes.
Co-own product and engineering roadmaps, balancing client commitments, reusable platform capabilities, technical investments, delivery risk, and team capacity.
Lead delivery from discovery through production deployment and ongoing support; develop estimates, staffing and implementation plans, and dependency plans.
Identify risks and tradeoffs early, make recommendations, and use client feedback, adoption, operational results, and engineering insights to guide priorities and continuous improvement.
Establish standards for coding, testing, documentation, version control, code review, release management, and software quality.
Guide technical decisions and the evolution of applications, APIs, shared services, data products, and client-specific configurations.
Ensure prototypes have a defined path to production rather than becoming unsupported standalone applications.
Oversee cloud, data, deployment, monitoring, and production practices with internal technology and governance teams to operate Sightline ADAPT securely and reliably.
Set an AI-first approach to software development, testing, documentation, operations, analytics, and product capabilities.
Help the team adopt AI-assisted engineering workflows while maintaining quality, privacy, security, intellectual-property protection, auditability, and human accountability.
Guide AI-enabled features, including evaluation, monitoring, data governance, and human oversight.
Evaluate emerging AI technologies and identify opportunities to improve the product or engineering effectiveness.
Serve as a senior technical authority in selected client meetings, demonstrations, discovery sessions, and solution reviews.
Translate client integration, security, data, and operational requirements into practical implementation approaches.
Support proposals, scopes of work, estimates, technical narratives, and delivery plans.
Communicate capabilities, limitations, dependencies, roadmap decisions, and delivery tradeoffs to technical, client, and executive audiences.
Build client confidence in ICF’s ability to deliver and support enterprise-scale analytical applications.