Senior AI Software Engineer & Developer

Job Type

Full-time

Description

NOTE: This opportunity is full-time employment position only (no 1099 or C2C engagements, or third parties or staffing agencies, please). The candidate MUST be a U.S. Citizen and Permanent Resident (Green Card holder). This is a remote opportunity; candidate must be based in the U.S.; have resided in the U.S. for at least 3 years in the past 5 years; ET time zone work schedule.

Daily Responsibilities

• Serve as a senior, hands-on full-stack AI engineer and technical authority, leading the technical strategy, design, and delivery of large-scale mission-critical AI systems supporting federal programs.

• Serve as the primary technical authority, defining AI and application architecture across multiple programs.

• Establish enterprise modernization roadmaps aligned to mission outcomes, compliance, and scalability.

• Lead architecture for distributed, cloud-native, and hybrid AI systems.

• Define and enforce reference architectures, standards, and reusable frameworks.

• Drive cross-program technical decision-making to ensure interoperability, security, and long-term sustainability.

• Advise senior federal stakeholders (SES-level and above) on AI adoption, modernization, and risk management.

• Lead design, development, and deployment of advanced AI solutions using Python as the primary development language, including large language models (LLMs) and foundation models, Retrieval-Augmented Generation (RAG) systems, agentic workflows, and orchestration frameworks.

• Architect and implement scalable ML systems and services built on Python-based frameworks and APIs.

• Build full-stack AI applications end to end, from user-facing interfaces to back-end services, APIs, and data layers.

• Integrate AI and LLM capabilities into existing enterprise applications and legacy platforms (e.g., content management, case management, and records systems) via APIs, middleware, and event-driven patterns.

• Define and implement distributed training strategies (GPU/TPU clusters, parallelization, optimization).

• Oversee full ML lifecycle in partnership with the senior data scientist: data pipelines, feature engineering, training, evaluation, deployment, and monitoring.

• Drive model optimization techniques (quantization, distillation, caching) to improve performance and cost.

• Establish robust MLOps practices leveraging Python-driven automation, pipelines, and tooling.

• Stand up the enterprise CI/CD-to-AI/MLOps pipeline, beginning with time-boxed proofs of concept and MVP implementations that mature into production systems.

• Serve as SME in federal AI policy (e.g., NIST AI RMF, OMB M-25-21 and M-25-22, Executive Order 14179).

• Define and operationalize Responsible AI frameworks, including model validation and evaluation, bias mitigation and fairness, and explainability, auditability, and safety.

• Ensure compliance with FISMA, FedRAMP, NIST 800-53, privacy, and Section 508 requirements.

• Lead large-scale modernization initiatives (e.g., legacy-to-cloud, microservices transformation, including Python-based refactoring and re-platforming efforts).

• Define repeatable modernization frameworks and accelerators.

• Oversee DevSecOps pipelines, CI/CD automation, zero-trust architectures, and secure software supply chain practices.

• Ensure delivery of resilient, high-availability systems in regulated federal environments.

• Lead multiple concurrent engineering efforts across integrated teams.

• Provide technical leadership to architects, engineers, and DevSecOps specialists, including establishing Python coding standards and engineering best practices.

• Mentor senior engineers and technical leaders; elevate engineering excellence and code quality.

• Support technical strategy in proposals, captures, and client engagements.

• Contribute to thought leadership (whitepapers, architecture patterns, platform strategy).

• Executive communication skills with experience influencing senior leaders.

Requirements

• Must of a U.S. Citizen or Permanent Resident (Green Card holder), as mandated by our government client.

• Must be able to complete/pass/hold at a minimum a Public Trust Investigation / background check. An active clearance (e.g. Public Trust, Secret, or higher) is preferred.

• Must be based / reside in the U.S.

• 12+ years of software engineering experience combining senior technical leadership, hands-on expertise in Python-based AI/ML systems (including large language models), and ownership of enterprise architecture, governance, and innovation.

• 8+ years of applied AI/ML experience, including building and deploying production systems (LLMs, generative AI, and large-scale or distributed model systems).

• Expert-level Python development experience, including designing production-grade ML systems, data pipelines, and microservices-based architectures.

• Hands-on experience with ML frameworks (PyTorch, TensorFlow, JAX) and distributed training (DeepSpeed, FSDP, Horovod).

• Full-stack engineering skills, including front-end frameworks, back-end services, RESTful APIs, microservices, and cloud-native deployment (e.g., containers, Kubernetes).

• Deep experience with cloud platforms (Azure, AWS, GCP), including FedRAMP environments and designing AI systems in cloud-native, distributed environments.

• Deep expertise in machine learning and deep learning, particularly transformer-based models and LLMs.

• Hands-on experience with LLM application stacks, including orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel), embeddings, vector databases, and prompt engineering.

• Experience with AI platforms and architectures (e.g., AWS Bedrock, Azure OpenAI Service, Google Vertex AI, RAG, agents).

• Proven success delivering enterprise-scale systems and modernization programs.

• Strong background in microservices, APIs, distributed systems, and DevSecOps practices.

• Experience managing GPU-based infrastructure or high-performance ML environments.

• Demonstrated ability to translate AI research into production system.

• Proven ability to integrate AI capabilities into existing and legacy enterprise systems (e.g., legacy CMS or COTS platforms) using APIs, middleware, connectors, and event-driven architectures.

• Strong understanding of large-scale data systems and ML evaluation methodologies.

• Experience working with sensitive data, including PII safeguards such as anonymization, masking, and data loss prevention.

• Experience with enterprise integration technologies, including REST/SOAP services, message queues, ETL pipelines, and SQL/NoSQL databases.

• Proficiency with managed generative AI services (e.g., AWS Bedrock, Azure OpenAI Service, Google Vertex AI) and integrating frontier models such as GPT, Claude, and Gemini.

• Demonstrated ability to own solutions end to end — from discovery and prototyping through production deployment, integration, and ongoing support.

• Ability to balance strategic vision with deep hands-on technical execution.

• Excellent analytical skills, attention to detail, and strong problem-solving abilities.

• Excellent communication and collaboration skills to communicate complex analytical insights to executive and non-technical stakeholders. Ability to translate ambiguous business questions into analytical solutions.

• BS or MS degree (preferred) in engineering, data science, computer science, statistics or related field.

The following experience is PREFERRED

• Experience with federal civilian agencies preferred.

Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. $155k -$189k.

Salary Description

$155k - $189k