Lead Software EngineerLocation: Arlington, VA (Hybrid, 3 days onsite) Duration: Long Term ContractWe are seeking a hands-on, technically strong Lead Software Engineer to drive the architecture, design, and development of our intelligent, agentic products/applications, AI-powered services, and platform capabilities powering the next-generation of experimentation platform. The ideal candidate is passionate about leveraging Generative AI, Large Language Models (LLMs), and cloud-native technologies to deliver production-grade solutions that drive innovation, developer productivity, and business impact.In this role you will help define and evolve system architecture and non-functional requirements—such as scalability, performance, security, and reliability—ensuring our solutions meet the highest engineering standards. As a technical leader, you will lead the design, development, and deployment of secure, scalable, and reliable AI-powered applications and agentic systems. You will be responsible for building intelligent solutions capable of reasoning, adapting to feedback, collaborating with human-in-the-loop processes, and delivering measurable business outcomes. You will guide cross-functional teams in building scalable services, APIs, and analytical capabilities that power our platform, leveraging technologies like Databricks and cloud platforms such as AWS and Azure. You will collaborate closely with your immediate team and partner with other development teams across programs to align on shared goals, define cross-cutting initiatives, and deliver cohesive, enterprise-grade solutions. You will also mentor engineers, work across global time zones, and champion engineering excellence through best practices in software development, observability, and continuous delivery.Our teams are small, agile, and empowered to choose the processes that work best for their goals. Every engineer contributes to the full development lifecycle—from ideation and design to implementation and testing—fostering a culture of ownership, innovation, and continuous improvement.Responsibilities:Design, develop, and deploy AI-powered products, intelligent agents, and agentic workflows utilizing Large Language Models (LLMs), retrieval systems, orchestration frameworks, tool-calling patterns, and context-aware workflows.Architect and implement advanced agentic systems incorporating planning, reasoning loops, memory management, grounding, evaluation frameworks, safety mechanisms, and human-in-the-loop controls.Lead the transition of AI solutions from proof-of-concept to production by establishing best practices for reliability, observability, performance, security, governance, and cost optimization.Develop scalable AI applications and developer productivity solutions using modern AI frameworks, SDKs, and orchestration platforms.Serve as a hands-on technical contributor, designing, coding, testing, debugging, and delivering production-quality software across the full engineering lifecycle.Build and evolve scalable services, APIs, and analytical capabilities using modern engineering practices, cloud platforms, and data technologies such as AWS, Azure, Databricks, Spark/PySpark, Python, Java and related frameworks.Partner closely with product managers, engineering teams, architects, data scientists, QA, security, and operations teams to translate business and functional requirements into robust technical solutions.Coordinate and lead technical execution across globally distributed engineering teams, ensuring alignment across regions, time zones, dependencies, design decisions, and delivery milestones.Drive architecture and design reviews, code reviews, technical decision-making, and engineering tradeoff discussions to ensure solutions are secure, resilient, observable, performant, maintainable, and aligned with enterprise standards.Drive engineering excellence through CI/CD automation, DevSecOps practices, automated testing, and AI-assisted software development workflows.Establish reusable platforms, frameworks, accelerators, and engineering capabilities that improve developer productivity and accelerate solution delivery across teams.Identify opportunities to improve platform scalability, reliability, developer productivity, operational readiness, and speed of delivery through modernization, automation, reusable patterns, and engineering best practices.Provide technical mentorship to junior and mid-level engineers through design guidance, code review, pairing, knowledge sharing, and modeling strong engineering judgment.Navigate ambiguity in complex initiatives by clarifying technical direction, decomposing large problems, identifying risks, and driving alignment across stakeholders.Champion a culture of engineering excellence, continuous improvement, ownership, collaboration, and high-quality delivery across the team and partner organizations.Qualifications:8+ years of software engineering experience delivering scalable, high-performance, and reliable software in an agile environment.Strong hands-on experience designing and building distributed systems, microservices, RESTful APIs, and cloud-native applications.Strong experience with data-intensive applications and analytics platforms; experience with Databricks, Spark, or PySpark is highly desirable.Hands-on experience with AWS and/or Azure, CI/CD, containerization, Kubernetes, observability, and modern software delivery practices.Ability to translate business and product requirements into scalable, secure, and maintainable technical solutions.Excellent collaboration and communication skills, with a proven ability to work effectively across engineering, product, architecture, data science, QA, and operations teams.Experience leading and coordinating technical initiatives across globally distributed teams spanning multiple regions and time zones.Passion for mentoring and developing engineers through technical guidance, design reviews, and knowledge sharing.Strong problem-solving skills with the ability to work through ambiguity, make sound technical decisions, and drive results through hands-on execution.Bachelor’s degree in Computer Science, Software Engineering, or a related technical field; advanced degree is a plus.Proven experience building and delivering AI-powered applications, intelligent agents, or generative AI solutions in enterprise environments.Strong understanding of agentic AI architectures, including workflow orchestration, reasoning frameworks, memory systems, grounding techniques, evaluation methodologies, and safety controls.Hands-on experience with modern AI frameworks, SDKs, orchestration platforms, vector databases, retrieval systems, and agent development tooling.Strong programming expertise in Java, Python, or equivalent backend technologies, with a track record of developing production-ready software.
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