Offer summary

Qualifications:

Bachelor’s Degree in Computer Science, Computer Engineering, Data Science, Computational Linguistics, or a related field; Master’s is a bonus., 1-3+ years of professional experience building and shipping ML or NLP systems, focusing on LLM-based or Generative AI solutions., Expertise in Python and strong software engineering fundamentals including data structures, algorithms, and CI/CD., Familiarity with modern ML/LLM tooling and experience deploying workloads to Azure or AWS..

Key responsibilities:

Research, design, and develop production-grade Generative AI and intelligent automation solutions.

Lead end-to-end development including data collection, model fine-tuning, and secure cloud deployment.

Implement LLMOps/MLOps pipelines for automated testing and monitoring.

Translate mission requirements into technical designs and contribute to the VITAL Innovation Lab roadmap.

Job description

Anika Systems is an outcome-driven technology solutions firm that guides federal agencies in solving complex business challenges and preparing for the future. Our services span AI Strategy, Data Intelligence, AI & Machine Learning, Intelligent Automation, Enterprise Platforms and Engineering, with a specialized focus on National Security and Federal Financial programs. We are dedicated to delivering forward-thinking solutions that accelerate the critical missions of our government clients. Through our VITAL Innovation Lab, we invest heavily in research and development to anticipate mission needs and deliver cutting edge solutions.

This position is currently remote; however, in accordance with federal contract requirements and company policy, there may be future changes to work location expectations. Candidates should be prepared for the possibility of a return to the office, either partially or fully, based on client directives, contractual obligations, or company policies. Any such changes will be communicated in advance.

Must be a U.S. Citizen with the ability to obtain and maintain a government suitability clearance.

Role Overview
As an AI Software Engineer you will translate emerging research into production ready, Generative AI capabilities that improve the way federal agencies serve the public. You will own the full lifecycle—from ideation and prototyping through cloud deployment and MLOps—while working in a small, highly collaborative team of engineers, data scientists, and domain experts.
Key Responsibilities

Research, design, and develop production grade Generative AI and intelligent automation solutions using LLMs, RAG pipelines, and vector databases.

Lead end to end development: data collection/cleansing, model finetuning, evaluation, optimization, containerization, and secure cloud deployment (Azure/AWS).

Implement LLMOps/MLOps pipelines for automated testing, bias detection, monitoring, and rollback.

Apply Responsible AI principles and federal compliance standards (e.g., NIST RMF, FedRAMP) throughout the solution lifecycle.

Translate vague mission requirements into technical designs; iterate quickly with stakeholders via agile ceremonies and rapid prototyping.

Contribute to the VITAL Innovation Lab roadmap by identifying research topics, publishing internal white papers, and presenting at communities of practice.

Minimum Qualifications

Education: Bachelor’s Degree in Computer Science, Computer Engineering, Data Science, Computational Linguistics, or a related field; Master’s is a bonus.

Experience: 1-3+ years of professional experience building and shipping ML or NLP systems, including focus on LLM based or Generative AI solutions.

Technical skills:
Expert Python and strong software engineering fundamentals (data structures, algorithms, testing, CI/CD, Git, containers).
Hands on with modern ML/LLM tooling (PyTorch or TensorFlow; LangChain, LangGraph, vector databases such as Pinecone, Azure AI Search, FAISS) and AI Agents.
Proven experience deploying workloads to Azure (preferred), AWS, or another major cloud provider.
Familiarity with DevOps/Infrastructure as Code (GitHub Actions, Terraform/Bicep, Docker/Kubernetes).
Strong written and verbal communication; ability to explain complex concepts to nontechnical audiences.