Agentic AI Engineer

Role Description

Join our Data Science Team! Our collaborative and diverse data science team is focused on helping organizations unlock business value through machine learning, analytics, generative AI, agentic AI systems, and intelligent automation. We work across industries including sustainment, logistics, industrial modernization, acquisition, cybersecurity, retail, and manufacturing to design and implement solutions that solve complex business challenges.

We are seeking an experienced Agentic AI Engineer who is passionate about emerging AI technologies and can bridge the gap between business objectives and practical AI implementation. The ideal candidate will bring deep technical expertise in LLMs, agentic architectures, and modern AI frameworks while helping clients identify high-value use cases and implement scalable, production-ready AI solutions.

Key activities include:

• Design, develop, and deploy AI solutions leveraging LLMs, RAG, and agentic AI architectures.
• Design, evaluate, and maintain a seamless generative pipeline that accepts user queries/prompts in conversational language, handles real-time prompt orchestration to generate safe SQL, extracts required insights, and reformats raw datasets into clean, actionable, human-readable answers.
• Evaluate business processes and identify opportunities where generative AI and autonomous agents can improve efficiency, decision-making, and customer outcomes.
• Architect multi-agent and agentic workflows using modern frameworks.
• Develop AI systems that effectively utilize tools, APIs, enterprise data sources, and external services to perform complex tasks.
• Implement prompt engineering, model evaluation, guardrails, observability, and governance practices for production AI applications.
• Build and optimize RAG pipelines, vector databases, knowledge retrieval systems, and semantic search capabilities.
• Assess emerging AI models and technologies to determine the most effective and cost-efficient solutions for client needs.
• Integrate AI capabilities into enterprise software ecosystems, cloud platforms, and business workflows.
• Design and implement AI monitoring, testing, evaluation, and continuous improvement processes.
• Collaborate with business stakeholders, solution architects, software engineers, and data scientists to deliver AI-driven solutions.
• Present AI concepts, recommendations, architectures, and implementation strategies to technical and executive audiences.

Qualifications

• Strong proficiency in Python and experience developing AI applications using modern AI and machine learning frameworks.
• Hands-on experience with LLM orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
• Experience with vector databases and retrieval technologies.
• Experience implementing APIs, microservices, and cloud-native AI solutions.
• Knowledge of prompt engineering, model fine-tuning, evaluation frameworks, and AI safety considerations.
• Strong problem-solving, systems-thinking, and analytical skills.
• Ability to identify and mitigate AI bottlenecks, optimize system latency and increase traceability and confidence when building on very large data lake architectures.
• Excellent verbal and written communication skills.
• B.S. in Computer Science, Information Technology, Statistics, Analytics, Mathematics, Engineering or related scientific field.
• Minimum of seven (7) years of experience performing data science in corporate setting.
• Minimum of two (2) years of hands-on experience building and deploying AI or machine learning solutions.
• Real world experience deploying production-level agentic workflows.
• Must have or be willing to obtain Secret Clearance (this requires US Citizenship).
• Acceptable candidates must successfully pass a drug test and background screen.

Requirements

• Highly collaborative and skilled at translating technical topics to non-technical users.
• Experience with fine-tuning open-source models and running AI workloads on private infrastructure.
• Experience with MLOps, LLMOps, and AI lifecycle management practices.
• M.S. and/or Ph.D. in engineering, computer science, or related scientific discipline preferred.

Benefits

• Market-competitive salary.
• Generous PTO package.
• Comprehensive medical, dental, vision, and life insurance plans.
• 401K.
• Short/long-term disability insurance.
• A fun and engaging culture.
• Training opportunities to keep you up to speed on the latest technologies.