Senior Applied AI Engineer

Neural Solutions; Maryland; On-site; USD 150,000 - 210,000; Full time

Job summary

Neural Solutions is seeking a Senior Applied AI Engineer to pioneer production-grade AI systems for cyber operations. You will architect scalable AI solutions, lead exploration into new AI applications, and design agent orchestration across multiple models and tools.

You have deep Python expertise, extensive production AI experience, and a strong track record delivering robust, fail-safe AI services. This role emphasizes practical, implementable AI in security contexts with high reliability.

Qualifications

• 12+ years of software engineering experience with Python.
• Extensive experience building and deploying AI-powered apps in production.
• Expert understanding of modern AI architectures (agents, RAG, chains, function calling).
• Proven success integrating multiple AI services and handling failure modes.
• Strong experience with MCP servers or similar serving infrastructure.
• Advanced prompt engineering skills with measurable results.
• Proficiency in resilient distributed systems and async workflows.
• Thorough understanding of AI model strengths and limitations across providers.
• Ability to rapidly prototype while maintaining production-quality standards.
• Demonstrated ability to solve novel technical problems without predefined solutions.
• Excellent debugging skills for unpredictable AI behaviors.

Responsibilities

• Architect and implement production-grade AI systems for cyber operations, ensuring scalability and reliability.
• Lead technical exploration into new AI applications, charting paths through untested solutions.
• Design and build agent orchestration systems coordinating multiple AI models and tools.
• Develop robust MCP server implementations as foundational infrastructure.
• Create advanced prompt engineering strategies and reusable patterns for cyber scenarios.
• Build fault-tolerant API integration layers that handle model failures and edge cases.
• Mentor junior engineers while maintaining a high level of personal contribution.
• Make architecture decisions balancing innovation and operational reliability.
• Drive technical discussions about AI capabilities, limitations, and strategy.
• Deliver proof-of-concepts showcasing groundbreaking capabilities.
• Establish best practices for AI development in cyber operations.

Skills

Python

Production AI

AI architectures

AI service integration

Education

B.S. in a technical discipline

Experience may substitute degree (4 extra years)

Tools

MCP servers

Job description

Description
We’re seeking a Senior Applied AI Engineer who doesn’t just implement AI solutions—you pioneer them. This role is for someone who views the current state of AI in cyber as primitive and is motivated to push into uncharted territory. You’re the type who built AI agents before they were trendy, who has strong opinions about prompt engineering, and who can architect systems others haven’t imagined yet.

Embedded with cyber units, you’ll be the force multiplier transforming how security professionals work. You’ll tackle problems without Stack Overflow answers, create systems that handle real operational complexity, and design AI integrations that perform reliably under pressure. This isn’t about applying known patterns; it’s about inventing new ones. We’re looking for someone with real-world experience pushing AI systems to production—someone who knows the difference between demo magic and operational reality and has the technical depth to solve problems where others give up.

Responsibilities

• Architect and implement production-grade AI systems for cyber operations, ensuring scalability and reliability
• Lead technical exploration into new AI applications, charting paths through untested solutions
• Design and build agent orchestration systems coordinating multiple AI models and tools
• Develop robust MCP server implementations as foundational infrastructure
• Create advanced prompt engineering strategies and reusable patterns for cyber scenarios
• Build fault-tolerant API integration layers that handle model failures and edge cases
• Mentor junior engineers while maintaining a high level of personal contribution
• Make architecture decisions balancing innovation and operational reliability
• Drive technical discussions about AI capabilities, limitations, and strategy
• Deliver proof-of-concepts showcasing groundbreaking capabilities
• Establish best practices for AI development in cyber operations

Required Skills & Experience

• 12+ years of software engineering experience with deep Python expertise
• Extensive experience building and deploying AI-powered apps in production
• Expert understanding of modern AI architectures (agents, RAG, chains, function calling)
• Proven success integrating multiple AI services and handling failure modes
• Strong experience with MCP servers or similar serving infrastructure
• Advanced prompt engineering skills with measurable results
• Proficiency in resilient distributed systems and async workflows
• Thorough understanding of AI model strengths and limitations across providers
• Ability to rapidly prototype while maintaining production-quality standards
• Demonstrated ability to solve novel technical problems without predefined solutions
• Excellent debugging skills for unpredictable AI behaviors

Nice to Have

• Direct experience applying AI to cybersecurity or intelligence problems
• Contributions to major AI frameworks or tools
• Experience fine-tuning models for specialized domains
• Background in developer tools or platform engineering
• Knowledge of adversarial AI and security concerns for AI systems
• Published research or talks on applied AI topics
• Experience leading technical efforts in ambiguous spaces
• Active involvement in the AI engineering community

Qualifications

• 12 years of relevant experience and a B.S. in a technical discipline
• (Four additional years of experience may substitute for a degree)