AI Engineer (Senior and staff)

Job Description

? Design, develop, and maintain production-grade AI applications and services using modern software engineering practices (CI/CD, testing, observability, cloud-native design). ? Define and implement foundational platforms (e.g., conversational bots, AI-powered search, unstructured data processing, GenBI) that are reusable and scalable across the enterprise. ? Lead architectural decisions, bringing best practices in software development lifecycle, explainability, and responsible AI. ? Lead cross functional team initiatives?embedded projects with business stakeholders?to rapidly build and deploy AI solutions that solve high-priority problems. ? Evaluate and integrate existing AI tools, frameworks, and APIs (e.g., LLMs, vector DBs, retrieval-augmented generation) into robust applications. ? Champion automation in workflows?from data ingestion and preprocessing to model integration and deployment. Define their success criterias, metrics and standard operation procedures. ? Partner with data scientists, product managers, and other engineers to ensure end-to-end delivery and reliability of AI products. ? Stay current with emerging AI technologies, but prioritize practical application and delivery over experimental research. ? Contribute to the internal knowledge base, tooling libraries, and documentation to scale engineering practices across the organization. ? Mentor other engineer and data scientists and provide technical leadership across projects, helping raise the bar for rigor and impact. --- Job Qualifications Required: ? 7+ years of professional software engineering experience; ability to independently design and ship complex systems in production. ? Strong programming skills in Python (preferred), Java, or similar languages, with experience in developing microservices, APIs, and backend systems. ? Solid understanding of software architecture, cloud infrastructure (AWS, Azure, or GCP), and modern DevOps practices. ? Experience integrating machine learning models into production systems (e.g., LLMs via APIs, fine-tuning, RAG patterns, embeddings, agents and crew of agents etc.). ? Experience with large language models (LLMs), vector-based search, retrieval-augmented generation (RAG), or unstructured data processing. ? Ability to move quickly while maintaining code quality, test coverage, and operational excellence. ? Strong problem-solving skills and a bias for action, with the ability to navigate ambiguity and lead through complexity. ? Strong experience with technical mentorship and cross-team influence. ? Ability to translate complex technical ideas into clear business insights and communicate effectively with cross-functional partners. Preferred: ? Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems. ? Experience using GenAI frameworks such as LlamaIndex, Crew AI, AutoGen, or similar agentic/LLM orchestration toolkits. ? Experience building reusable modeling components or contributing to internal ML platforms. ? Background in working with embedded teams or in forward-deployed environments where rapid iteration and close business collaboration are key. ? Proficiency in Python and common ML/data science libraries (e.g., scikit-learn, pandas, NumPy, PyTorch, TensorFlow). ? Solid knowledge of machine learning fundamentals, including supervised and unsupervised learning, model evaluation, and statistical inference. ? Exposure to working with unstructured data (documents, conversations, images) and transforming it into usable structured formats. ? Experience building chatbots, search systems, or generative AI interfaces. ? Background in working within platform engineering or internal developer tools teams.