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/TypeScript (for API development), C++ (for performance-critical components).
- Frameworks and Libraries:
- Machine Learning: PyTorch, TensorFlow, JAX.
- Reinforcement Learning: Stable-Baselines3, Ray RLlib, OpenAI Gym, or Gymnasium.
- Agentic AI Frameworks: LangChain, LlamaIndex, AutoGen, or CrewAI.
- API Development: FastAPI, Flask, or Node.js.
- Cloud Platforms: AWS (SageMaker, Lambda, Bedrock), Google Cloud AI, Azure AI.
- Containerization: Docker, Kubernetes.
- Version Control: Git, GitHub, or GitLab.
- Databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, DynamoDB).
- DevOps Tools: CI/CD pipelines (Jenkins, GitHub 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.
Top Skills
What We Do
AnaVation is a trusted partner that delivers high-value, cost-effective solutions to solve our customers’ most complex technical and analytical problems.
AnaVation believes that the future of securing, collecting, processing, and analyzing cyber data will require the development of advanced ANAlytical technologies derived via the innoVATION of current and future technologies.
AnaVation believes in the “Idea of the Possible” — that it is possible for our experts, partnering with our customers in the right environment, to create innovative technical solutions that expand our customers’ capabilities.
We want to do two things for our customers. We want to resolve existing challenges and we want to prepare them for the future. Our technical expertise and innovative engineering culture enable us to do those things.








