Role Description We are seeking an AI Software Engineer with strong full‑stack engineering capabilities and hands-on experience integrating Generative AI technologies into real-world solutions. This role is ideal for engineers who excel in software development fundamentals, enjoy solving complex client challenges, and are passionate about leveraging modern AI tools to deliver meaningful business outcomes. The ideal candidate brings a strong balance of engineering rigor, rapid learning, ownership, and the ability to translate technical solutions into clear, client-ready outputs. Success in this position requires not only technical excellence but also adaptability, client empathy, and the communication and collaboration skills needed to drive impact in dynamic, fast-paced environments. This role plays a key part in designing, building, and deploying production-ready AI-powered applications within the Azure ecosystem. Qualifications - Professional experience applying AI in real-world, production use cases, not just experimentation or personal projects. - Experience designing and architecting AI workflows and AI pipelines in client or enterprise environments including patterns such as RAG, agentic systems, and multi-model orchestration. - Advanced prompt engineering skills and experience implementing LLM evaluations. - Ability to design end-to-end AI architectures on cloud platforms (Azure preferred) composing AI services for inference, search, and document processing. - Understanding of core AI model training concepts: train/validation/test splits, bias-variance tradeoff, model complexity tuning, and evaluation strategy. - Deep expertise in backend development using .NET or Python, with strong frontend capabilities in React or Angular. - Ability to define and champion project structure, module boundaries, and coding standards for large-scale codebases. - Experience leading technical decisions on architecture, patterns, and conventions for a project team. - Strong command of OOP principles, SOLID, and design patterns applied naturally and able to coach others on their appropriate use. - Experience with SQL, NoSQL, and vector databases designing data models that support AI features and efficient retrieval at scale. Requirements - Proven ability to design scalable, resilient systems choosing the right cloud services, architectural patterns, and infrastructure for the problem at hand. - Ability to evaluate and articulate trade-offs between cost, performance, complexity, and maintainability. - Experience with Infrastructure as Code (Terraform, Bicep, or similar) treating infrastructure with the same rigor as application code. - Experience designing cloud-native solutions that leverage the right tool for the job: compute, storage, messaging, caching, networking rather than defaulting to familiar patterns. - Confident leading technical discussions with clients independently presenting solution options, trade-offs, and recommendations clearly. - Ability to bridge business and technical language understanding client problems deeply enough to propose the right technical approach, and explaining technical decisions in terms clients trust. - Experience contributing to presales and requirements gathering providing credible technical input that shapes new engagements. Benefits - Coaches and mentors junior and mid-level engineers conducting impactful code reviews, pair programming sessions, and career conversations that drive real growth. - Develops career growth plans with team members, helping them identify their strengths, close gaps, and progress through their career levels. - Fosters a collaboration and knowledge-sharing environment running knowledge sessions, promoting best practices, and creating spaces where engineers learn from each other. - Builds community within the practice someone who naturally brings people together, creates psychological safety, and makes the team a place people want to be part of. - Runs parts of practice operations contributing to onboarding processes, team rituals, practice standards, and the operational rhythms that keep the group effective. - Works across disciplines collaborates effectively across Data, AI, and Software teams to deliver integrated solutions. Mindset, Attributes & Soft Skills The ideal candidate demonstrates a strong ownership mindset, taking responsibility for deliverables, following through on commitments, and consistently ensuring high‑quality outcomes. They show agency by proactively identifying opportunities, proposing solutions, and driving initiatives forward, while maintaining accountability and a high standard of professional integrity. With a clear focus on delivering measurable business value and client satisfaction, they quickly absorb new technologies, business domains, and client environments. They also leverage AI-assisted tools to enhance development speed, creativity, and overall solution quality. In addition to these attributes, the candidate excels in communication—able to explain complex technical concepts clearly to both technical and non-technical audiences, and presenting information in a compelling, client-ready manner. They are effective at client engagement, skilled in translating business needs into precise technical requirements and managing expectations throughout a project lifecycle. Collaboration comes naturally, allowing them to work seamlessly with cross-functional teams including product managers, business stakeholders, and technical leaders. Their adaptability enables them to shift quickly between industries and client contexts, particularly within a consulting environment. They are comfortable gathering requirements, understanding constraints, and shaping solutions that align with client objectives. Above all, they demonstrate professionalism through reliable communication, structured thinking, and consistent delivery in every aspect of their work. If you’re eager to push the boundaries of Generative AI, continuously learn, and contribute to high-impact technical solutions, we encourage you to apply and be part of our journey.