FREE ACCESS
5,000–10,000 jobs/day
See all jobs on JobTailor
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Tech Stack
Tools & technologiesAWSAzureCloudDistributed SystemsGoogle Cloud PlatformMicroservices
About the role
Key responsibilities & impact- 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.
- Coordinate 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
What you’ll need- 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.
- Ability to travel as required by project needs.
Benefits
Comp & perks- The opportunity to support high visibility federal missions in IT and healthcare
- A culture that values innovation, growth, collaboration, and quality
- Access to cutting-edge tools and technologies
- Comprehensive benefits for you and your family
- A career path that rewards ambition and performance
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Software EngineeringMachine LearningData EngineeringGenerative AI SolutionsDistributed SystemsAPIsMicroservicesCloud-Native ApplicationsTechnical DirectionArchitecture Reviews
Soft Skills
CommunicationLeadershipStakeholder ManagementConsultingMentoring