AI Engineer

• Python
• AI/ML frameworks (TensorFlow / PyTorch)
• LLMs & Generative AI
• Prompt Engineering
• RAG & Vector Databases
• AI Platform Experience (OpenAI, Hugging Face, Anthropic)
• Prototyping & AI Tool Development
• LangChain / CrewAI
• AWS Bedrock / Azure AI
• MLOps & CI/CD
• LoRA Fine-Tuning
• Agentic AI Systems
• Open-source contributions

We are looking for a driven and technically proficient AI Engineer who thrives on the latest AI innovations, quick iteration, and converting innovative concepts into practical applications that enhance AI integration throughout our client's business processes.

This position reports to the AI Product & Research Manager and involves investigating advancements in Generative AI, creating initial prototypes, and partnering with development teams to evolve these into robust, deployable solutions.

Key Responsibilities

AI Innovation and Technology Assessment

• Stay abreast of developments in AI and Machine Learning, emphasizing Generative AI, large language model structures, agent-based systems, and multi-modal approaches.
• Assess new technologies, libraries, and interfaces including platforms like ChatGPT, GitHub Copilot, LangChain, LangSmith, CrewAI, vector stores, retrieval-augmented generation tools, workflow managers, and model deployment services.
• Pinpoint areas where innovative AI features can address operational challenges or improve efficiency in the client's environment.

Rapid Prototyping & Hands-On Development

• Construct efficient, operational prototypes with a strong hands-on coding approach in Python, utilizing contemporary AI toolkits and model APIs.
• Create trial functionalities and ideas to confirm viability prior to handover to production engineering groups.
• Develop, evaluate, and refine AI processes, data pipelines, autonomous systems, and applications enhanced by retrieval mechanisms.

Experimentation and Evaluation

• Perform comparative testing, model assessments, prompt optimization, and adjustment trials to measure effectiveness.
• Analyze various models, tools, and designs to suggest optimal solutions for implementation teams.
• Record outcomes clearly, including experiment records, performance overviews, replicable scripts, and detailed technical write-ups.

Teamwork with Developers and Partners

• Collaborate directly with development groups to convert prototypes into reliable, production-grade platforms.
• Convert test results into practical guidance on system design, resources, and deployment strategies.
• Interact with product leads, business collaborators, and analytics experts to ensure prototypes meet practical requirements.

Innovation Advocacy and Information Dissemination

• Monitor industry trends, scholarly publications, community contributions, and competitive advancements.
• Deliver presentations, demonstrations, and suggestions to technical executives and key stakeholders.
• Promote an environment of AI advancement via training sessions, guides, and shared internal resources.

Required Qualifications

Technical Proficiency and Investigative Skills

• Degree in Computer Science, Artificial Intelligence, Data Analytics, or equivalent field (or comparable background).
• Over 5 years of direct involvement in AI development, investigative roles, ML experimentation, or related positions.
• Advanced coding skills in Python and knowledge of primary AI/ML environments (e.g., TensorFlow, PyTorch).
• Hands-on involvement with LLMs, prompt refinement, retrieval-augmented systems, LangChain, LangSmith, CrewAI, vector databases, and similar contemporary Generative AI resources.
• Track record in developing rapid prototypes, proofs-of-concept, and trial AI tools.

Practical AI and Ecosystem Familiarity

• Thorough insight into AI landscapes like OpenAI, Anthropic, Hugging Face, Azure AI, AWS Bedrock, and comparable services.
• Experience with development aids such as GitHub Copilot, AI-assisted coding tools, and current MLOps practices.
• Ease in delving into model mechanics, tuning parameters, integrating APIs, and using assessment tools.

Interpersonal Abilities and Team Dynamics

• Proven skill in adapting advanced research ideas into viable technical implementations.
• Superior writing and presentation abilities for audiences ranging from experts to generalists.
• Inquisitive approach with dedication to ongoing exploration, testing, and skill enhancement.
• Capacity to handle various investigative paths, iterations, and evolving priorities.

Preferred Qualifications

• Background in model customization, LoRA techniques, or custom model training.
• Expertise in agentic AI systems, automation frameworks, and workflow orchestration.
• Prior experience publishing research insights or contributing to open-source AI projects.
• Certifications in specialized AI/ML subjects or cloud-based AI environments.