Senior Software Engineer - Artificial Intelligence (AI) & ML

Description & Requirements

The AI Engineer will design, develop, and implement machine learning solutions, support AI initiatives for our IRS client, and contribute to innovative projects.

Position is fully remote.

Candidates in the Washington DC area are preferred in case there is a need to attend onsite client meetings.

The selected candidate must be able to obtain and wait for the completion of an interim Minimum Background Investigation (MBI) clearance prior to starting employment.

This process may take approximately 3-4 months.

Essential Duties and Responsibilities:
- Lead, develop, collaborate, and advance the applied and responsible use of AI, ML, mathematical, and data science solutions throughout the enterprise by finding the right fit of tools, technologies, methodologies, processes, and automation to enable effective and efficient solutions for each unique situation.

Lead the use of applied mathematical analyses to provide solutions.
- Lead efforts across the enterprise to support the creation of solutions and real mission outcomes, emphasizing and teaching the ability to flex and demonstrate initiative when dealing with ambiguous and fast-paced situations.
- Act as technical translator and role model for effectively articulating and translating technical needs, solutions, outputs, and impacts to all levels, regardless of technical proficiency, in a respectful, collaborative, and situationally appropriate manner.
- Maintain deep, current knowledge of the AI technology landscape and emerging developments, evaluating their applicability for use in production/operational environments.
- Lead the creation, curation, and promotion of playbooks, best practices, lessons learned, and firm intellectual capital.

Job-Specific Essential Duties and Responsibilities:

- Design, develop, and deploy (AI) Machine Learning, Deep Learning models that support business objectives and enhance product functionality.

- Demonstrated knowledge in designing, building, testing, and deploying machine models.

- Collaborate with software engineers and data scientists to integrate trained models into production environments and ensure scalable performance.

- Proficient in using Python, have good working knowledge of R, and other programming languages to develop data pipelines, preprocessing routines to clean up data, and model automation workflows as needed.

- Apply knowledge of data structures, algorithms, and statistics to ensure model accuracy, efficiency, and reliability.

- Work with large language models (LLMs) such as ChatGPT, Gemini, or Meta LLMs, including OpenAI API integration and prompt optimization.

- Preferably to have worked with LangChain family of products, MCP, and other integration technologies with databases and other knowledge artifacts

- Implement and maintain MLOps practices for continuous training, deployment, and monitoring of AI models.

- Evaluate and adopt emerging AI tools, frameworks, and methodologies to
improve system per...