Lead Forward Deployed Engineer (FDE)

About the role

The Lead Forward Deployed Engineer (FDE) at LTS provides technical leadership for the design, development, and deployment of AI-powered software solutions addressing complex business and mission challenges. This role combines AI engineering, software architecture, solution delivery, and technical program leadership.

Responsibilities

• Serve as the primary technical advisor for customer engagements, building trusted relationships with executive leadership, technical stakeholders, and business owners.
• Lead technical discovery sessions, solution workshops, and architecture discussions to define customer objectives and implementation strategies.
• Translate business priorities into scalable AI-enabled software solutions and technical roadmaps.
• Advise customers on AI adoption strategies, solution architecture, governance, and operational readiness.
• Communicate complex technical concepts, trade-offs, and implementation risks to both technical and non-technical audiences.
• Support business development activities through technical presentations, demonstrations, proof-of-concepts (POCs), proposals, and solution briefings.
• Lead cross-functional engineering teams responsible for delivering enterprise AI and software solutions.
• Provide technical direction throughout the full software development lifecycle, from architecture through deployment and operational support.
• Guide engineering teams in designing secure, scalable, maintainable, and high-performing software systems.
• Lead architecture reviews, design discussions, sprint planning, technical decision-making, and engineering governance.
• Establish engineering standards, development practices, quality metrics, and delivery processes across engagements.
• Remove technical blockers, manage delivery risks, and ensure successful execution across multiple projects or workstreams.
• Mentor engineers through architecture guidance, code reviews, technical coaching, and career development.
• Architect and oversee the development of AI-enabled applications, intelligent automation solutions, and modern software platforms.
• Lead the design and implementation of solutions leveraging large language models (LLMs), retrieval-augmented generation (RAG), agentic AI, machine learning, and other emerging AI technologies.
• Guide the design of scalable data pipelines, knowledge retrieval systems, APIs, microservices, and enterprise integrations.
• Establish best practices for prompt engineering, AI evaluation, model governance, human-in-the-loop workflows, and responsible AI.
• Define engineering approaches that balance scalability, performance, security, reliability, governance, and cost.
• Review production-quality code and ensure adherence to software engineering best practices.
• Drive implementation of CI/CD pipelines, automated testing, monitoring, logging, observability, and operational excellence.
• Develop reusable frameworks, technical accelerators, documentation, and engineering standards that improve delivery across programs.
• Lead multiple engineering initiatives while ensuring consistent delivery quality across teams.
• Cook up cross-functional and geographically distributed engineering teams, including hybrid onshore/offshore delivery models.
• Establish delivery governance, resource planning, risk management, stakeholder communications, and project health reporting.
• Contribute to organizational engineering strategy, AI capability development, and technical innovation.
• Promote continuous improvement through engineering best practices, reusable assets, and knowledge sharing.
• Stay current on emerging AI technologies, cloud platforms, software engineering trends, and industry best practices.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related technical discipline (or equivalent experience).
• 7+ years of experience in software engineering, AI engineering, machine learning, data engineering, solution architecture, or related technical roles.
• Demonstrated experience leading engineering teams delivering enterprise software solutions.
• Experience designing, building, and deploying AI/ML or Generative AI solutions in production environments.
• Experience architecting distributed systems, APIs, microservices, cloud-native applications, or enterprise integrations.
• Strong experience with cloud platforms such as AWS, Microsoft Azure, Google Cloud Platform, or hybrid cloud environments.
• Experience leading technical workstreams and translating business objectives into scalable technology solutions.
• Experience implementing CI/CD pipelines, DevOps practices, automated testing, and production monitoring.
• Excellent communication, leadership, consulting, and stakeholder management skills.
• Proven ability to lead engineering teams in agile environments while remaining hands-on technically.

Qualifications

• N/A

Skills

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Benefits

LTS offers comprehensive benefits for you and your family, including access to cutting-edge tools and technologies.

Pay

LTS shares salary ranges to promote transparency. Final compensation may vary based on experience, skills, location, and role requirements.

Schedule

N/A