Job Description

SAIC is seeking a high performing group of individuals for AI genetic solution to work closely with our government customer. We're building a powerful team of forward-thinking professionals skilled in Agentic AI solutions, cutting-edge engineering, and scalable cloud architectures.

These roles may not be immediately available.

We're seeking motivated, multidisciplinary individuals to join one of the following key roles within our team:

Agentic AI Solutions Product Manager

As a Solutions Product Manager, you'll define and drive the strategy for AI-native and agentic solutions, working with cross-functional teams to design and deliver human-agent collaboration models while ensuring measurable mission and business value.

Responsibilities include:

• Crafting agent behaviors, workflow orchestration frameworks, and AI governance guardrails.
• Leading the creation of implementation plans, user experiences, and operational workflows for AI solutions.
• Facilitating stakeholder engagement and aligning solution strategies with organizational goals.
• Skills and expertise: Agile product management, prompt design, business process transformation, experimentation (e.g., A/B testing), and usage of platforms such as LLMs, RAG, MCP, and other multi-agent systems.
• Experience: 8+ years in product/program management, digital/cloud transformation, including 3+ years in AI solutions and adoption.

Agentic AI Solutions Orchestrator

As the Solutions Orchestrator behind multi-agent system architectures, you'll lead the end-to-end engineering and deployment of complex AI ecosystems.

Responsibilities include:

• Designing, implementing, and governing multi-agent workflows and architecture(e.g., LangGraph, AutoGen, CrewAI).
• Orchestrating a **dynamic portfolio of AI agents**, fostering collaboration between multiple agent systems and AIs.
• Building reusable components for rapid deployment and integration with cloud platforms.
• Skills and expertise: Strong systems thinking, prompt design, multi-agent framework architecture, and experience with cloud-native platforms.
• Experience: 8+ years in IT solutions architecture, with 3-5+ years focused on AI, cloud, and automation systems.

Agentic AI-Native Engineer (Mid to Senior)

Ready to utilize your full-stack engineering expertise to build and optimize production-scale AI-native systems?

Responsibilities include:

• Architecting and deploying agent-based systems with a strong focus on production-grade engineering and continuous improvement.
• Leveraging Model Context Protocol (MCP), CI/CD pipelines, API design, and cloud-native tools for agile, iterative development cycles.
• Critically reviewing and optimizing AI-generated outputs for maximum efficiency, quality, and usability.
• Skills and expertise: Spec coding, autonomous agents, cloud deployment systems, automated workflows, and LLM integration.
• Experience: 5-8+ years in software engineering, cloud-native development, APIs, and AI/automation systems.

Agentic AI Quality & Spec Engineer (Mid to Senior)

As the Quality & Spec Engineer you'll be the bridge between business needs and technical execution, you'll ensure AI-driven systems achieve flawless quality and outcomes in alignment with user requirements.

Responsibilities include:

• Translating intent into actionable AI-consumable workflows, specifications, blueprints, and test cases.
• Designing intelligent test generation systems to ensure automated decision processes align with business goals.
• Ensuring test cases, validations, and regulations are built into the core of automated AI systems.
• Skills and expertise: QA automation, testing frameworks, prompt engineering, agentic workflow design, and AI-driven quality engineering.
• Experience: 5-8+ years in quality assurance, SDLC, and automation.

Agentic AI Platform Engineer (Mid to Senior)

As the AI platform engineer, you'll architect and maintain the infrastructure that enables scalable and secure AI operations.

Responsibilities include:

• Designing and managing stable, secure agent execution environments, deployment pipelines, and cloud-native infrastructures.
• Implementing robust FinOps, IAM and security protocols, agent governance guardrails, and observability for Agentic AI platforms.
• Leveraging LLMOps platforms for managing complex multi-agent systems and workloads across cloud environments (AWS, Azure, GCP).
• Skills and expertise: Kubernetes/container orchestration, CI/CD automation, FinOps, data pipelines, and DevOps methodologies.
• Experience: 5-8+ years in DevOps, cloud/platform engineering, Kubernetes, and AI/LLMOps platforms.

For these roles we're looking for individuals with:

• A deep passion for applying AI, machine learning, and advanced engineering methodologies to practical, real-world problems.
• Collaborative mindsets with the ability to work across cross-disciplinary teams, including data science, product management, engineering, and client stakeholders.
• A strong grasp of large language models (LLMs), AI governance, and advanced frameworks like LangGraph, CrewAI, Multi-Agent orchestration, MCP, and code generation tools.
• Experience navigating cloud-native environments like AWS, Azure, and Google Cloud, and an eagerness to stay ahead of emerging technologies.

Qualifications

TYPICAL EDUCATION AND EXPERIENCE: Bachelors and five (5) years or more experience; Masters and three (3) years or more experience; PhD and 0 years related experience

Additional relevant years and/or certifications will be considered in lieu of education