Principal Software Engineer

We are assisting our client in their search for a Principal Sofware Engineer. This is a long term, remote, contract opportunity.

As a Principal Sofware Engineer, you will lead the design, implementation, and optimization of their data infrastructure to support advanced AI initiatives. This role emphasizes expertise in data pipelines, machine learning integration, and emerging AI technologies such as prompt engineering and agentic AI systems. You will collaborate with cross-functional teams to ensure data reliability, scalability, and ethical AI practices, driving projects from conception to production.

Responsibilities List

• AI Strategy Development: Develop and communicate the enterprise AI vision, strategy, and principles, with an emphasis on agentic AI and prompt engineering, aligning with business objectives. Define the target state AI roadmap, identifying opportunities for AI-driven innovation, optimization, and transformation through autonomous agents.
• Technical Mentorship and Leadership: Provide technical leadership and mentorship to development teams, guiding them in agentic AI design principles, prompt engineering best practices, and emerging AI technologies.
• Foster a culture of innovation, collaboration, and continuous learning to drive AI excellence with a hands-on approach.
• Hands-On Development: Conduct code reviews for AI agents, prototype agentic workflows and prompt chains, build reference AI code, and when required, help deliver AI software in a collaborative fashion with development teams, focusing on prompt optimization and agent autonomy.
• AI Governance: Establish and enforce AI governance processes, standards, and best practices to ensure consistency, ethical use, and compliance across AI projects, including guidelines for prompt engineering and agentic behavior.
• Business Capability Enhancement: Define and maintain models that integrate agentic AI into business processes, functions, and information flows. Analyze and optimize business capabilities using AI agents and prompt engineering to drive efficiency, agility, and innovation.
• AI Technology Portfolio Management: Manage the organization's AI technology portfolio, including agentic frameworks, LLMs, platforms, and supporting components. Conduct AI technology assessments, rationalization, and modernization efforts to optimize the AI stack and support business goals through advanced prompt engineering.
• Cloud-Native AI Development: Develop and communicate cloud-native AI strategies, patterns, and practices, focusing on agentic AI. Define and design AI automation processes using DevOps practices and a Platform as a Product approach to support agentic applications and service implementations, incorporating prompt engineering for scalable AI interactions.
• AI Integration: Define AI integration standards to enable seamless data exchange and interoperability across systems, applications, and platforms, with a focus on agentic workflows. Design and implement integration solutions that support real-time data sharing, AI-driven business process automation, and digital transformation initiatives using optimized prompts.
• AI Technology Evaluation: Evaluate new and emerging AI technologies, frameworks, and tools, including advancements in agentic AI and prompt engineering, to assess their suitability for adoption. Create AI design patterns, prompt templates, and reference implementations to validate choices and make recommendations based on technical merit, cost, and strategic alignment.

Key Skills:

• Extensive experience in AI system design and development, with a focus on building scalable, high-performance, and resilient agentic AI systems using advanced prompt engineering techniques.
• Deep understanding of AI development methodologies, frameworks, and patterns, including agentic architectures, large language models (LLMs), multi-agent systems, and event-driven AI.
• Proficiency in evaluating and selecting appropriate AI technologies, platforms, and tools to support business objectives and technical requirements, with expertise in prompt optimization and agent orchestration.
• Strong communication and collaboration skills, with the ability to engage effectively with stakeholders at all levels of the organization on AI-related topics.
• Leadership abilities, including mentoring, coaching, and influencing cross-functional teams and stakeholders in AI and prompt engineering practices.
• Analytical and problem-solving skills, with the ability to analyze complex AI problems, debug agentic behaviors, and develop innovative prompt-based solutions.
• Knowledge of regulatory requirements, compliance standards (e.g., AI ethics, data privacy), and industry best practices relevant to agentic AI development.

Technologies/Tools:

• AI development tools (e.g., LangChain, CrewAI, AutoGen) for building and documenting agentic AI workflows and prompt chains.
• Collaboration platforms (e.g., Confluence, Draw.io, Miro) for sharing AI documentation and facilitating collaboration on prompt engineering.
• Knowledge of a wide range of AI technologies, platforms, and tools relevant to enterprise AI development, including programming languages (e.g., Python), LLMs (e.g., GPT models, Llama), cloud AI services (e.g., AWS Bedrock, Azure AI), vector databases (e.g., Pinecone), and middleware for agentic systems.