Requirements

Expected technologies

AWS

Python

Our requirements

…we expect you to be able to demonstrate the following key competencies:

Impactful

Proactive in identifying what needs to be done, and taking action, before being asked, or before the situation escalates. Identifies, resolves problems, and removes obstacles that could hinder project’s success & progress.

Curious

Engages in learning activities and is interested in understanding different ways of doing things including the key activities performed by others in the team. Keeps up to date on relevant frameworks, applications, software, and/or tools.

Collaborative

Partners with a range of people to create trust and co-create and deliver mutually beneficial outcomes. Collaborates in a thoughtful manner and values others’ unique contributions.

Communication

Communicates clearly and actively listens to others. Concise in communicating and references relevant information tailored to the audience to support points.

Adaptable

Demonstrates flexibility in adapting to changing situations, tools and priorities. Quickly learns and applies new tools, technologies and processes as needed.

You will require the following qualifications and skills

6+ years of experience in AI and machine learning, out of which 3+ years of experience in machine learning engineering, NLP, Generative AI, and LLM technologies. Experience with LLM Agentic workflows and frameworks (Langchain, LangGraph, LlamaIndex, etc.). Knowledge and experience with transformer architectures, prompt engineering, retrieval-augmented generation (RAG), guardrails, and LLM evaluation methodologies. Proficiency in spoken and written English at a minimum B2/C1 level. Hands-on experience of MLOps and LLMOps is desired. Knowledge of design, implementation and management of distributed training pipelines for LLMs to ensure scalability and efficiency are nice to have. Advanced knowledge of Python and some experience in ML frameworks (PyTorch, scikit-learn, etc.) for training, fine-tuning, and deploying generative models is desired. Experience with Cloud technology, preferably AWS. Experience with Voice Conversational AI will be a big plus. Ability to contribute both independently and as part of a team. Excellent analytical and problem-solving skills. Excellent listening, communication, interpersonal and presentation skills to articulate complex technical ideas to cross-disciplinary internal and external stakeholders.

Your responsibilities

• Building and integrating generative AI applications for customer interactions by using LLMs and orchestration frameworks.
• Driving the design, development and scaling of internal AI agents and customer-facing agentic solutions such as GenAI-powered Contact Centers.
• Designing and deploying custom solutions on AWS Bedrock by using foundation models from leading providers.
• Fine-tuning and evaluating large language models by using proprietary and external datasets.
• Building scalable APIs and backend services to support real-time AI inference.
• Ensuring reliability, privacy, and accuracy of Gen AI responses by applying testing and monitoring tools.
• Contributing to governance efforts by ensuring generative AI solutions follow responsible AI principles, including transparency, data privacy, and compliance with industry standards.
• Working with the data science team to apply generative AI to other business areas, including document processing, claims decisioning, and reporting.
• Supporting bolttech global GenAI roadmap bringing expert insights on the technology to adopt.
• Documenting solutions and collaborating with engineering, product, and customer teams to align requirements and output.
• Tracking industry trends and recommending tools or approaches to improve system performance and capability.