Lead Software Engineer - AI Solutions

We are seeking a highly skilled Lead Software Engineer - AI Solutions with strong expertise in Full Stack Software Development, Solution Design, Cloud Engineering, Data Engineering, and AI application development.

This is a hands-on technical leadership role for an experienced engineer who combines deep software engineering expertise with the ability to lead the design and delivery of scalable, enterprise-grade solutions.

Key Responsibilities

• Lead the design, development, and delivery of scalable enterprise applications, APIs, and services.
• Drive technical solution design and contribute to architectural decisions across products and platforms.
• Collaborate with Product Owners and stakeholders to translate business requirements into scalable technical solutions.
• Provide technical leadership and guidance to engineering teams throughout the software development lifecycle.
• Lead design reviews, code reviews, and technical discussions to ensure engineering quality and consistency.
• Design and implement microservices, integrations, reusable frameworks, and cloud-native applications.
• Ensure software solutions meet security, compliance, performance, scalability, and reliability requirements.
• Partner with DevOps teams to implement CI/CD pipelines, deployment automation, observability, and operational best practices.
• Drive continuous improvement initiatives related to software architecture, development standards, testing, and operational excellence.
• Mentor and coach Associate and Senior Software Engineers while fostering a culture of collaboration, innovation, and engineering excellence.
• Evaluate emerging technologies and recommend improvements that enhance product capabilities and development efficiency.
• Act as the primary technical point of contact for delivery teams and provide guidance for resolving complex technical challenges.

AI Responsibilities

• Lead the design and implementation of AI-powered applications and intelligent automation solutions.
• Design scalable Retrieval-Augmented Generation (RAG) architectures and enterprise knowledge retrieval solutions.
• Build and deploy AI-enabled services leveraging Large Language Models (LLMs), vector databases, and AI orchestration frameworks.
• Define engineering standards and best practices for Generative AI development across teams.
• Guide the implementation of prompt engineering strategies, evaluation frameworks, and AI observability practices.
• Collaborate with architects, data engineers, and business stakeholders to identify and prioritize AI use cases.
• Evaluate emerging AI technologies, frameworks, and tools, recommending practical adoption strategies.
• Design integrations between AI platforms, enterprise systems, APIs, and data sources.
• Ensure AI solutions align with security, compliance, responsible AI, and data governance requirements.
• Mentor engineering teams on AI development patterns, framework selection, and implementation best practices.
• Drive the adoption of reusable AI accelerators, agent workflows, and scalable AI engineering patterns.

Requirements / Skills

• Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, or a related field.
• 8-12 years of professional software engineering experience.
• Strong hands-on experience developing and delivering enterprise-scale applications using Python and/or Java.
• Proven experience designing distributed systems, APIs, microservices, and cloud-native architectures.
• Strong experience building modern web applications using React or similar front-end frameworks.
• Solid understanding of enterprise integration patterns, software architecture principles, and system design methodologies.
• Experience working with Microsoft Azure (preferred) and/or AWS cloud platforms.
• Strong experience with DevOps practices including CI/CD pipelines, containerization, Kubernetes, Infrastructure as Code, and deployment automation.
• Familiarity with Azure DevOps, GitHub Actions, Terraform, and modern software delivery practices.
• Experience working with relational databases, NoSQL databases, and enterprise data platforms.
• Strong analytical, troubleshooting, and problem-solving abilities.
• Excellent communication and stakeholder management skills with the ability to engage effectively with technical and non-technical audiences.
• Demonstrated experience mentoring engineers and leading technical initiatives.

Preferred AI Skills & Experience

• Hands-on experience designing and deploying Generative AI solutions in production environments.
• Strong understanding of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and AI orchestration patterns.
• Experience working with frameworks such as LangChain, Semantic Kernel, LlamaIndex, AutoGen, CrewAI, or similar technologies.
• Experience integrating solutions using Azure OpenAI, Azure AI Foundry, AWS Bedrock, Anthropic, OpenAI APIs, or equivalent AI platforms.
• Experience with vector databases, embeddings, semantic search, knowledge retrieval systems, and AI evaluation frameworks.
• Understanding of prompt engineering, model evaluation, AI observability, and performance optimization techniques.
• Familiarity with emerging AI interoperability standards such as MCP (Model Context Protocol) and agent communication patterns.
• Experience building AI-enabled workflows, intelligent automation solutions, and enterprise AI integrations.
• Exposure to Snowflake, Databricks, modern data engineering platforms, and AI/ML infrastructure is highly desirable.