Forward Deployed Engineer (Applied AI), Senior

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 a Forward 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

LCG's 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 today's stack.

Key Responsibilities

Required Qualifications

• Bachelor's 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.

• Master's 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 $135,000 to $152,000 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 hr@lcginc.com.

Securing Your Data

Beware of fraudulent job offers using LCG's name. LCG will never request payment-related details or advancement of money during the application process. Legitimate communication will only come from lcginc.com or system@hirebridgemail.com emails, not free commercial services like Gmail or WhatsApp. If you receive suspicious emails asking for payment or personal information, contact us immediately at hr@lcginc.com.

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 candidate's 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.