Artificial Intelligence Engineer

Job Summary
1. Role DescriptionWe are seeking a highly technical and execution-oriented Manager of Intelligent Automation to lead and drive a portfolio of AI, automation, data analytics, and machine learning initiatives. This role is designed for a hands-on technical leader who can translate business needs into scalable AI-enabled solutions, guide technical design, build prototypes, evaluate tools, and accelerate delivery across multiple initiatives.Although people management could be part of the job, this position is not a people management role. Instead, the Manager of Intelligent Automation will serve as a technical owner, solution driver, and program execution lead for an AI portfolio that includes machine learning, data analytics, intelligent automation, generative AI, RAG-based applications, agentic AI, and AI-assisted software delivery.The ideal candidate combines strong programming skills, applied AI/ML knowledge, data engineering awareness, and practical experience delivering automation and analytics solutions in enterprise environments.
2. Job Duties and ResponsibilitiesLead the technical execution of AI and Intelligent Automation initiatives, from pilots and proofs of concept to production-ready solutions.Identify, assess, prioritize, and structure AI, automation, analytics, and data-driven opportunities in partnership with business and technology stakeholders.Design, prototype, and support AI/ML, GenAI, RAG, agentic AI, automation, and data analytics solutions using modern frameworks, cloud services, APIs, and programming tools.Establish reusable technical patterns, standards, accelerators, and responsible AI practices covering governance, security, privacy, explainability, monitoring, and value measurement.Track portfolio execution, risks, dependencies, blockers, adoption, and business outcomes while communicating technical concepts clearly to engineering teams and executive stakeholders.
3. Primary Skills1. Applied AI / Machine Learning EngineeringStrong hands-on capability in designing, developing, evaluating, and deploying AI/ML solutions using Python and modern machine learning frameworks. Must understand model development, feature engineering, model evaluation, experimentation, and practical application of ML to business problems.2. Data Analytics, Data Engineering, and Insight GenerationStrong ability to work with structured and unstructured data, including SQL, data preparation, ETL/ELT concepts, data quality, analytics modeling, dashboarding, and business insight generation. Must be able to connect data pipelines and analytical outputs to measurable business value.3. Programming, Automation, and AI Solution DevelopmentStrong programming skills, preferably in Python, with the ability to build prototypes, APIs, automation scripts, AI-enabled workflows, integrations, and production-oriented technical solutions. Experience with AI-assisted coding, software engineering practices, and automation frameworks is highly valuable.
4. Additional Technical Skills
Strong hands-on programming experience with Python, SQL, APIs, automation scripting, data processing, and solution prototyping.Experience developing AI/ML solutions using frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar technologies.Practical knowledge of Generative AI, LLM APIs, prompt engineering, RAG patterns, vector search, embeddings, and LLM evaluation techniques.Exposure to agentic AI, AI-assisted coding, automation platforms, and orchestration frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, UiPath, or Power Automate.Understanding of cloud platforms, MLOps/LLMOps, CI/CD, Git-based development, API integration, secure delivery practices, dashboards, and analytics tools.
5. Preferred Qualifications5+ years of experience in intelligent automation, data analytics, machine learning, software engineering, data engineering, or AI solution delivery.Bachelor’s degree in Computer Science, Data Science, Engineering, Information Systems, Statistics, Mathematics, or a related technical field.Demonstrated experience leading technical initiatives, AI pilots, automation programs, or data-driven transformation efforts.Experience working in enterprise environments with cross-functional teams, including business stakeholders, architects, engineers, security teams, and operations teams.Proven ability to move from problem discovery to prototype, solution design, implementation support, and measurable value realization.Experience managing a portfolio of initiatives, including prioritization, roadmap development, dependency tracking, risk management, and executive reporting.Strong analytical thinking, technical curiosity, and ability to solve ambiguous problems through experimentation and iterative delivery.Ability to evaluate emerging AI technologies and determine their practical applicability to business and operational challenges.Experience applying responsible AI, security, compliance, and governance considerations to AI-enabled solutions.Excellent communication skills, with the ability to translate technical concepts into business impact and executive-level recommendations.