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Senior AI Software Engineer

Job in Chantilly, Fairfax County, Virginia, 22021, USA
Listing for: Nava
Full Time position
Listed on 2026-02-28
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Software Engineer
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

Be Challenged and Make a Difference

In a world of technology, people make the difference. We believe if we invest in great people, then great things will happen. At Ana Vation, we provide unmatched value to our customers and employees through innovative solutions and an engaging culture.

Description of Task to be Performed

Ana Vation is seeking a Senior Agentic-AI Software engineer to join our team that will design, develop, and deploy advanced Agentic AI systems that autonomously perform complex tasks, make decisions, and interact with dynamic environments. You will collaborate with cross-functional teams to deliver scalable, efficient, and ethical AI solutions that drive business impact. You will architect and implement agentic AI systems capable of autonomous decision-making, task planning, and execution in real-world applications.

Design and integrate multi-agent systems to solve complex problems through collaborative and competitive interactions. Develop and fine-tune large language models (LLMs) and reinforcement learning (RL) models to power agentic behaviors. Implement robust APIs and interfaces to integrate AI agents with external systems, databases, and tools. Optimize AI models for performance, scalability, and low-latency inference in production environments. Conduct rigorous testing, validation, and monitoring of AI agents to ensure reliability, safety, and alignment with ethical standards.

Collaborate with product managers, data scientists, and software engineers to define requirements and deliver end-to-end AI solutions. Stay updated on the latest advancements in Agentic AI, LLMs, and RL, and incorporate cutting‑edge techniques into development workflows. Mentor junior developers and contribute to knowledge‑sharing within the team.

Required Qualifications
  • Clearance
    :
    Active TS/SCI within last 24 months
  • Education
    : BA/BS is Computer Science or another related field
  • Experience
    : BS + 10 Yrs or MS + 8 Yrs experience in computer science, AI, Machine Learning, or a related field.
  • 5+ years of experience in AI/ML development, with at least 2 years focused on Agentic AI or autonomous systems.
  • Proven track record of deploying production‑grade AI systems, including framework experience such as AWS Bedrock.
  • Strong problem‑solving skills and ability to work in a fast‑paced, collaborative environment.
Preferred Qualifications
  • PhD in computer science, AI, Machine Learning, or a related field
  • Technology Stack:
  • Programming

    Languages:

    Python (primary), JavaScript/Type Script (for API development), C++ (for performance‑critical components).
  • Frameworks and Libraries:
  • Machine Learning:
    PyTorch, Tensor Flow, JAX.
  • Reinforcement Learning:
    Stable‑Baselines3, Ray RLlib, OpenAI Gym, or Gymnasium.
  • Agentic AI Frameworks:
    Lang Chain, Llama Index, Auto Gen, or CrewAI.
  • API Development:
    FastAPI, Flask, or Node.js.
  • Cloud Platforms: AWS (Sage Maker, Lambda, Bedrock), Google Cloud AI, Azure AI.
  • Containerization:
    Docker, Kubernetes.
  • Version Control:
    Git, Git Hub, or Git Lab.
  • Databases: SQL (Postgre

    SQL, MySQL), No

    SQL (Mongo

    DB, Dynamo

    DB).
  • Dev Ops Tools: CI/CD pipelines (Jenkins, Git Hub Actions), monitoring tools (Prometheus, Grafana).
  • AI Models and Techniques:
  • Large Language Models (LLMs):
    Experience with models like LLaMA, GPT, BERT, or Grok for natural language understanding and generation, including leveraging AWS Bedrock for LLM deployment and management.
  • Reinforcement Learning (RL):
    Expertise in RL algorithms (e.g., DQN, PPO, SAC) and multi‑agent RL systems.
  • Agentic AI Paradigms:
  • Knowledge of goal‑driven agents, task decomposition, and autonomous planning (e.g., ReAct, Plan‑and‑Execute architectures).
  • Prompt Engineering:
  • Designing prompts for LLMs to achieve reliable and context‑aware outputs, optimized for Bedrock's model ecosystem.
  • Model Fine‑Tuning:
  • Techniques like LoRA, QLoRA, or full fine‑tuning for domain‑specific applications, with experience using Bedrock for fine‑tuning workflows.
  • Evaluation Metrics:
  • Familiarity with BLEU, ROUGE, perplexity, and custom metrics for agent performance.
Benefits
  • Generous cost sharing for medical insurance for the employee and dependents
  • 100% company paid dental insurance for employees and dependents
  • 100%…
Position Requirements
10+ Years work experience
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