Hi,

Hope you are doing good, this is Rajeev from FutureTech Consultants, LLC and I have a job opening with our direct client.

Please have a look at the below job description and let me know your interest. Please share me the latest copy of your resume.

Role: Generative AI Engineer

Location: Washington, DC / Rockville, MD / McLean, VA (Hybrid 3 days onsite)

Duration: 6 Months with Possible Extension

Interview Type: 1^st Round Video & Final Round On-Site

Job Summary:

• We are seeking an accomplished Software Engineer with a strong interest in Generative AI to help identify, develop, and implement AI-driven solutions across the software development lifecycle (SDLC).
• This role combines hands-on software engineering with AI enablement.
• The ideal candidate has strong technical judgment, understands modern development practices, and can identify where AI and automation can meaningfully improve developer productivity and engineering workflows.
• In addition to building and prototyping solutions, this individual will serve as a technical advisor and educator, helping engineering teams adopt AI-enhanced development practices through demonstrations, training, workshops, documentation, and community-building initiatives.

Key Responsibilities

GenAI & Engineering Enablement

• Partner with software engineers, technical leaders, and internal users to identify opportunities for AI-driven improvements across the SDLC.
• Design, prototype, test, and implement AI-enabled development solutions and automation.
• Evaluate emerging GenAI tools and determine where they can provide meaningful value to engineering teams.
• Apply strong engineering and product judgment when determining what to automate and how solutions should be designed.
• Integrate AI capabilities into existing development workflows, tools, and processes.
• Identify and correct low-quality or inaccurate AI-generated code and technical content.
• Troubleshoot technical challenges related to AI tool adoption and integration.
• Serve as a technical advisor on AI development tools, implementation patterns, and best practices.
• Rapidly evaluate and incorporate new AI capabilities as technologies evolve.

Technical Enablement & Content Development

• Develop technical enablement materials covering software development best practices, GenAI integration, development tools, processes, and standards.
• Create content for multiple learning formats, including instructor-led sessions, self-service resources, workshops, and hands-on labs.
• Partner with subject matter experts, engineers, architects, and technical leaders to develop and validate content.
• Gather requirements and identify engineering pain points, training needs, and automation opportunities.
• Maintain and continuously improve technical content as AI tools and engineering practices evolve.
• Build relationships across engineering teams to encourage adoption of new tools and development practices.
• Measure the effectiveness of enablement initiatives through feedback, assessments, adoption, and performance metrics.

Training & Technical Presentations

• Lead technical training sessions, workshops, and demonstrations for engineering and technology audiences.
• Present to audiences ranging from small development teams to larger organizational groups.
• Demonstrate AI-enabled development tools, workflows, and engineering best practices.
• Translate complex technical concepts into clear, practical guidance for audiences with varying levels of technical expertise.

Required Qualifications

• 5+ years of hands-on software development experience.
• Strong understanding of the software development lifecycle, including Agile development, DevOps, CI/CD, Git/version control, testing strategies, and deployment practices.
• Hands-on programming experience and the technical depth to engage directly with software engineering teams.
• Experience using or integrating Generative AI and AI-assisted development tools into software engineering workflows.
• Understanding of AI-powered coding and development tools, such as Kiro or similar AI coding assistants.
• Ability to critically evaluate AI-generated code and content for accuracy, quality, security, and maintainability.
• Experience developing, prototyping, and implementing technical solutions in partnership with cross-functional teams.
• Strong understanding of modern development tools, cloud technologies, and deployment platforms.
• Advanced technical problem-solving and troubleshooting skills.
• Ability to gather requirements and translate engineering needs into practical solutions.
• Experience working in rapidly changing technical environments and evaluating emerging technologies.

Communication & Collaboration

• Strong presentation and public-speaking skills, particularly with technical audiences.
• Ability to explain complex engineering and AI concepts clearly to engineers, business partners, and leadership.
• Strong written communication, technical documentation, and instructional-content development skills.
• Ability to influence and build relationships across teams without direct authority.
• Comfortable facilitating workshops, technical demonstrations, and hands-on learning sessions.
• Collaborative mindset with an emphasis on building solutions alongside engineering teams rather than simply documenting existing processes.

Preferred Qualifications

• Experience with engineering enablement, developer productivity, internal developer platforms, or developer tooling.
• Experience designing or delivering technical training programs.
• Experience implementing AI-assisted development practices within an enterprise environment.
• Familiarity with cloud-based software architectures and modern DevOps practices.
• Experience working within a regulated or highly controlled technology environment.
• Demonstrated ability to rapidly learn and apply emerging technologies.
• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related technical discipline.
• Relevant cloud, DevOps, software development, or AI certifications are a plus.

Ideal Candidate

• The ideal candidate is a hands-on engineer who is excited about the potential of Generative AI but approaches it with strong technical judgment.
• You understand that successful AI adoption requires more than introducing new tools it requires identifying the right use cases, validating AI-generated outputs, integrating solutions into existing engineering workflows, and helping developers understand how to use these capabilities effectively.
• You are intellectually curious, comfortable experimenting with emerging technologies, and able to move quickly from idea to prototype.
• You are equally comfortable writing code, demonstrating a new AI-enabled workflow, collaborating with engineers and architects, and presenting technical concepts to a broader audience.

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