Forward Deployed Engineer (Applied AI), Senior
Job Location:
Rockville, MD - USA
Yearly Salary:
Posted:
Application Deadline:
Vacancies:
Job Summary
Location: Rockville MD (A minimum of 1 day - potentially more depending on clients needs)
Required Clearance: Ability to obtain Public Trust
Sponsorship: No sponsorship assistance is available for this position now or in the future.
Position Description:LCG is seeking aForward Deployed Engineer (FDE) to embed directly in federal client environments and deliver applied AI outcomes not just recommendations. Working side by side with client teams this engineer designs prototypes evaluates and ships AI solutions that solve real operational and mission challenges carrying them from prototype to production to scale.
This role is ideal for a hands-on AI professional who can work directly with clients understand business needs identify where AI can create measurable value and rapidly translate those needs into working solutions. The FDE will serve as the AI expert embedded across multiple client projects partnering with engineering teams business stakeholders and leadership to advance AI adoption improve workflows and modernize existing systems.
The successful candidate will bring strong experience in AI/ML Python LLMs Advance RAG model evaluation and agentic coding tools. This person should be comfortable operating in ambiguous environments communicating with technical and non-technical stakeholders and mentoring teams on practical AI use cases and responsible AI practices.
The LCG Forward Deployed Model
LCGs FDEs are our differentiator: They define how we show up for our clients. Modeled on the leaner embedded delivery approach commercial firms use this role brings proven commercial AI practices into government. Federal clients today want more than recommendations; they want someone who can deliver outcomes quickly working shoulder to shoulder with their teams. Our FDE pair consulting judgment with engineering skill: They can dig into the data and build a working solution one day then put on a suit and brief an executive the next.
- Embed and observe: Sit side by side with client teams to learn their workflows firsthand including what tools they use who they coordinate with and how decisions get made across meetings and stakeholders.
- Split your time deliberately: Spend it in roughly equal measure across client engagement end-user research business context and hands-on building staying boots on the ground to get it done.
- Deliver outcomes: Focus on rapid measurable delivery getting working product into users hands week over week and refining it against their feedback.
- Co-create in cross-functional pods: Operate in pods rather than isolated builds using continuous feedback loops and agile frameworks to test evaluate and scale AI solutions directly against business outcomes.
- Trace data and decisions: Understand where data comes from which stakeholders own it and what decisions the system needs to capture turning many meetings into a clear picture of the decisions that matter.
- Drive change management: Help clients rethink how work has been done so tasks that were once manual or slow no longer have to be even inside sensitive and secure environments.
- Balance leadership and the ground: Build the focused piece that shows clear value to leadership while staying embedded with end users and engineers.
- Bring it back: Capture what works and return it to LCG as reusable frameworks and accelerators that speed up the next engagement.
- Adapt continuously: Learn and adopt new tools as the landscape shifts rather than relying only on todays stack.
Key Responsibilities
- Lead discovery with federal clients to understand mission needs workflows and constraints and translate ambiguous problems into well-scoped measurable AI use cases.
- Identify where AI creates measurable value communicate capabilities and risks to technical and non-technical stakeholders and partner with LCG leadership to align solutions with modernization strategy.
- Own end-to-end delivery building and validating prototypes with Python LLMs advanced RAG and agentic frameworks then moving proven solutions through production to scale.
- Integrate AI into existing systems and workflows alongside engineering DevSecOps data and security teams and lead change management for adoption in secure environments.
- Evaluate model and system performance establish baselines and apply responsible AI practices producing governance artifacts suitable for client review.
- Serve as an embedded AI subject matter expert mentoring teams and capturing reusable frameworks and accelerators for future engagements.
Required Qualifications
- Bachelors degree in Computer Science Engineering Data Science Artificial Intelligence or a related field plus 5 years of hands-on experience in AI/ML engineering data science or software engineering.
- Strong Python development experience.
- Hands-on experience with Generative AI LLMs RAG and prompt engineering including at least one agentic or LLM application framework.
- Experience with cloud AI platforms such as AWS AI/ML Amazon Bedrock SageMaker Azure AI or Azure OpenAI and integrating AI with APIs enterprise systems and operational workflows.
- Familiarity with Git CI/CD secure development practices and modern SDLC processes.
- Hands-on experience with agentic coding tools and the judgment to evaluate AI-generated result.
- Ability to communicate effectively with technical teams business stakeholders and client leadership and to operate independently in fast-moving ambiguous environments.
- Ability to obtain and maintain a Public Trust clearance.
- Masters degree in Computer Science Data Science Artificial Intelligence Machine Learning or a related field.
- Experience with GraphRAG advanced RAG hybrid search re-ranking MCP tool-use patterns and enterprise AI integrations.
- Experience with model tuning techniques such as LoRA/QLoRA fine-tuning distillation pruning or quantization plus data science statistical modeling and model performance evaluation.
- Experience delivering AI solutions in federal regulated healthcare financial or other high-compliance environments including FedRAMP-authorized or secure federal cloud delivery.
- Experience producing model cards evaluation reports and responsible AI artifacts supporting AI adoption or enablement and working in startup consulting product or other fast-paced delivery environments.
- Strong applied AI engineering depth with the ability to design build evaluate and improve AI systems.
- Strong business translation skills with the ability to turn client needs into practical AI use cases.
- Strong communication skills and ability to influence teams without formal authority.
- Strong mentoring mindset and ability to teach developers how to apply AI tools effectively.
- Strong evaluation mindset including the ability to question AI-generated outputs and validate quality.
- Comfortable balancing experimentation with production readiness.
- Ability to work directly with clients and internal teams to identify value define scope and deliver measurable outcomes.
- Innovative proactive and comfortable working in undefined or evolving environments.
- Python plus LangChain AutoGen CrewAI LlamaIndex LangGraph or similar.
- RAG and retrieval: Advance RAG GraphRAG embeddings vector databases hybrid search and re-ranking.
- Cloud AI platforms: Amazon Bedrock Microsoft Foundry Google Vertex AI.
- Integration and governance: APIs MCP tool-use patterns cloud services enterprise workflow integrations model evaluation frameworks and AI governance documentation.
Compensation and Benefits
The projected compensation range for this position is $135000 to $152000 per year benchmarked in the Washington D.C. metropolitan area. The salary range provided is a good faith estimate representative of all experience levels. Salary at LCG is determined by various factors including but not limited to role location the combination of education/training knowledge skills competencies certifications and work experience.
LCG offers a competitive comprehensive benefits package which includes health insurance options (medical dental vision) life and disability insurance retirement plan contributions as well as paid leave federal holidays professional development and lifestyle benefits.
Devoted to Fair and Inclusive Practices
All qualified applicants will receive consideration for employment without regard to sex race ethnicity age national origin citizenship religion physical or mental disability medical condition genetic information pregnancy family structure marital status ancestry domestic partner status sexual orientation gender identity or expression veteran or military status or any other basis prohibited by law.
If you are interested in applying for employment with LCG and need special assistance or an accommodation to apply for a posted position contact our Human Resources department by email at .
Securing Your Data
Beware of fraudulent job offers using LCGs name. LCG will never request payment-related details or advancement of money during the application process. Legitimate communication will only come from or emails not free commercial services like Gmail or WhatsApp. If you receive suspicious emails asking for payment or personal information contact us immediately at .
If you believe you are the victim of a scam contact your local law enforcement and report the incident to the U.S. Federal Trade Commission.
Use of Artificial Intelligence in Recruiting
LCG may use artificial intelligence (AI) and other automated technologies to support portions of the recruiting and hiring process including resume review candidate matching interview scheduling skills assessment and other administrative functions. AI-assisted tools are used solely to support our hiring process and do not independently determine employment outcomes. Final hiring decisions are made by trained hiring professionals following a comprehensive review of each candidates qualifications. We are committed to equal employment opportunity and strive to ensure our hiring practices are fair transparent and compliant with applicable laws. Applicants needing a reasonable accommodation during the application or interview process should contact Human Resources.
Location: Rockville MD (A minimum of 1 day - potentially more depending on clients needs)
Required Clearance: Ability to obtain Public Trust
Sponsorship: No sponsorship assistance is available for this position now or in the future.
Position Description:LCG is seeking aForward Deployed Engineer (FDE) to embed directly in federal client environments and deliver applied AI outcomes not just recommendations. Working side by side with client teams this engineer designs prototypes evaluates and ships AI solutions that solve real operational and mission challenges carrying them from prototype to production to scale.
This role is ideal for a hands-on AI professional who can work directly with clients understand business needs identify where AI can create measurable value and rapidly translate those needs into working solutions. The FDE will serve as the AI expert embedded across multiple client projects partnering with engineering teams business stakeholders and leadership to advance AI adoption improve workflows and modernize existing systems.
The successful candidate will bring strong experience in AI/ML Python LLMs Advance RAG model evaluation and agentic coding tools. This person should be comfortable operating in ambiguous environments communicating with technical and non-technical stakeholders and mentoring teams on practical AI use cases and responsible AI practices.
The LCG Forward Deployed Model
LCGs FDEs are our differentiator: They define how we show up for our clients. Modeled on the leaner embedded delivery approach commercial firms use this role brings proven commercial AI practices into government. Federal clients today want more than recommendations; they want someone who can deliver outcomes quickly working shoulder to shoulder with their teams. Our FDE pair consulting judgment with engineering skill: They can dig into the data and build a working solution one day then put on a suit and brief an executive the next.
- Embed and observe: Sit side by side with client teams to learn their workflows firsthand including what tools they use who they coordinate with and how decisions get made across meetings and stakeholders.
- Split your time deliberately: Spend it in roughly equal measure across client engagement end-user research business context and hands-on building staying boots on the ground to get it done.
- Deliver outcomes: Focus on rapid measurable delivery getting working product into users hands week over week and refining it against their feedback.
- Co-create in cross-functional pods: Operate in pods rather than isolated builds using continuous feedback loops and agile frameworks to test evaluate and scale AI solutions directly against business outcomes.
- Trace data and decisions: Understand where data comes from which stakeholders own it and what decisions the system needs to capture turning many meetings into a clear picture of the decisions that matter.
- Drive change management: Help clients rethink how work has been done so tasks that were once manual or slow no longer have to be even inside sensitive and secure environments.
- Balance leadership and the ground: Build the focused piece that shows clear value to leadership while staying embedded with end users and engineers.
- Bring it back: Capture what works and return it to LCG as reusable frameworks and accelerators that speed up the next engagement.
- Adapt continuously: Learn and adopt new tools as the landscape shifts rather than relying only on todays stack.
Key Responsibilities
- Lead discovery with federal clients to understand mission needs workflows and constraints and translate ambiguous problems into well-scoped measurable AI use cases.
- Identify where AI creates measurable value communicate capabilities and risks to technical and non-technical stakeholders and partner with LCG leadership to align solutions with modernization strategy.
- Own end-to-end delivery building and validating prototypes with Python LLMs advanced RAG and agentic frameworks then moving proven solutions through production to scale.
- Integrate AI into existing systems and workflows alongside engineering DevSecOps data and security teams and lead change management for adoption in secure environments.
- Evaluate model and system performance establish baselines and apply responsible AI practices producing governance artifacts suitable for client review.
- Serve as an embedded AI subject matter expert mentoring teams and capturing reusable frameworks and accelerators for future engagements.
Required Qualifications
- Bachelors degree in Computer Science Engineering Data Science Artificial Intelligence or a related field plus 5 years of hands-on experience in AI/ML engineering data science or software engineering.
- Strong Python development experience.
- Hands-on experience with Generative AI LLMs RAG and prompt engineering including at least one agentic or LLM application framework.
- Experience with cloud AI platforms such as AWS AI/ML Amazon Bedrock SageMaker Azure AI or Azure OpenAI and integrating AI with APIs enterprise systems and operational workflows.
- Familiarity with Git CI/CD secure development practices and modern SDLC processes.
- Hands-on experience with agentic coding tools and the judgment to evaluate AI-generated result.
- Ability to communicate effectively with technical teams business stakeholders and client leadership and to operate independently in fast-moving ambiguous environments.
- Ability to obtain and maintain a Public Trust clearance.
- Masters degree in Computer Science Data Science Artificial Intelligence Machine Learning or a related field.
- Experience with GraphRAG advanced RAG hybrid search re-ranking MCP tool-use patterns and enterprise AI integrations.
- Experience with model tuning techniques such as LoRA/QLoRA fine-tuning distillation pruning or quantization plus data science statistical modeling and model performance evaluation.
- Experience delivering AI solutions in federal regulated healthcare financial or other high-compliance environments including FedRAMP-authorized or secure federal cloud delivery.
- Experience producing model cards evaluation reports and responsible AI artifacts supporting AI adoption or enablement and working in startup consulting product or other fast-paced delivery environments.
- Strong applied AI engineering depth with the ability to design build evaluate and improve AI systems.
- Strong business translation skills with the ability to turn client needs into practical AI use cases.
- Strong communication skills and ability to influence teams without formal authority.
- Strong mentoring mindset and ability to teach developers how to apply AI tools effectively.
- Strong evaluation mindset including the ability to question AI-generated outputs and validate quality.
- Comfortable balancing experimentation with production readiness.
- Ability to work directly with clients and internal teams to identify value define scope and deliver measurable outcomes.
- Innovative proactive and comfortable working in undefined or evolving environments.
- Python plus LangChain AutoGen CrewAI LlamaIndex LangGraph or similar.
- RAG and retrieval: Advance RAG GraphRAG embeddings vector databases hybrid search and re-ranking.
- Cloud AI platforms: Amazon Bedrock Microsoft Foundry Google Vertex AI.
- Integration and governance: APIs MCP tool-use patterns cloud services enterprise workflow integrations model evaluation frameworks and AI governance documentation.
Compensation and Benefits
The projected compensation range for this position is $135000 to $152000 per year benchmarked in the Washington D.C. metropolitan area. The salary range provided is a good faith estimate representative of all experience levels. Salary at LCG is determined by various factors including but not limited to role location the combination of education/training knowledge skills competencies certifications and work experience.
LCG offers a competitive comprehensive benefits package which includes health insurance options (medical dental vision) life and disability insurance retirement plan contributions as well as paid leave federal holidays professional development and lifestyle benefits.
Devoted to Fair and Inclusive Practices
All qualified applicants will receive consideration for employment without regard to sex race ethnicity age national origin citizenship religion physical or mental disability medical condition genetic information pregnancy family structure marital status ancestry domestic partner status sexual orientation gender identity or expression veteran or military status or any other basis prohibited by law.
If you are interested in applying for employment with LCG and need special assistance or an accommodation to apply for a posted position contact our Human Resources department by email at .
Securing Your Data
Beware of fraudulent job offers using LCGs name. LCG will never request payment-related details or advancement of money during the application process. Legitimate communication will only come from or emails not free commercial services like Gmail or WhatsApp. If you receive suspicious emails asking for payment or personal information contact us immediately at .
If you believe you are the victim of a scam contact your local law enforcement and report the incident to the U.S. Federal Trade Commission.
Use of Artificial Intelligence in Recruiting
LCG may use artificial intelligence (AI) and other automated technologies to support portions of the recruiting and hiring process including resume review candidate matching interview scheduling skills assessment and other administrative functions. AI-assisted tools are used solely to support our hiring process and do not independently determine employment outcomes. Final hiring decisions are made by trained hiring professionals following a comprehensive review of each candidates qualifications. We are committed to equal employment opportunity and strive to ensure our hiring practices are fair transparent and compliant with applicable laws. Applicants needing a reasonable accommodation during the application or interview process should contact Human Resources.
Required Experience:
IC
