Senior Gen AI Engineer
Join Genese as a Senior Gen AI Engineer and build scalable AI agents, RAG systems, and LLM-powered solutions. Work remotely with advanced AI models, AWS services, and modern frameworks while contributing to real-world generative AI applications across cloud, data, and digital transformation projects.
Reports to: Technical Consultant
Shift: Monday to Friday, Remote
Time: 2-10PM
Position Overview
Genese solution is seeking a highly skilled and motivated AI/ML Engineer with a strong foundation in programming and data engineering. The ideal candidate will be responsible for designing, developing, and deploying AI/ML models while ensuring seamless data integration and pipeline optimization. The role requires a blend of hands-on machine learning expertise and software engineering proficiency to drive intelligent insights and business solutions.
The ideal candidate will be responsible for architecting, developing and deploying AI systems by evaluating business needs and recommending optimal approaches like RAG, fine-tuned models, traditional ML, multi-agent frameworks, or hybrid solutions.
The role requires a blend of hands-on machine learning expertise and software engineering proficiency to drive intelligent insights and business solutions.
Roles and Responsibilities
Key Responsibilities:
- Building complex multi-agent AI agents that are highly scalable
- Work with LLMs, embedding models, and Retrieval-Augmented Generation (RAG) systems.
- Engineer and refine prompts to enhance AI performance and output quality.
- Deploy and scale AI solutions using AWS (Lambda, cloud services) and modern architectures.
- Ensure AI applications align with ethical standards, data privacy, and real-world scalability.
- Develop, fine-tune, and optimize generative AI models using TensorFlow, PyTorch, or Hugging Face.
Desired Skills, Expertise and Knowledge:
- Work with current state of the art LLMs and embedding models.
- Experience building agentic AI systems.
- Experience with debugging traces of LLM calls to identify errors/optimizations.
- Experience with building Retrieval-Augmented Generation (RAG) systems.
- Engineer and refine prompts to enhance AI performance and output quality.
- Knowledge of extracting structured outputs from LLMs.
- Experience using LLM APIs, embedding models, and RAG-based AI architectures.
- Strong skills in Python, AI model deployment, and AWS services (Lambda preferred).
- Knowledge of LangChain, Pydantic, and scalable AI workflows.
- Proficiency in prompt engineering and optimization techniques.
- Some UI/UX experience is a plus.
Preferred Qualifications:
Preferred:
- Experience in NLP, computer vision, or multimodal AI.
- Proven track record of deploying AI solutions at scale.
- Research background in generative AI models.
What We Offer
- Work in a multinational company operating in the Cloud & ICT domain, based out of the UK and operating in Australia, India, Nepal, Pakistan, and Bangladesh
- Best in class open, progressive, professional, and equal opportunity work environment
- Closely knit and supportive team members and a culture where your contributions, opinions, and diversity is welcome, respected, & encouraged
- Exposure to multi-disciplinary skill areas (including team management & leadership) in a vibrant start-up ecosystem with deep work involving world-class leaders like Amazon, Microsoft, Google, Alibaba, DigitalOcean, and Facebook
- Opportunity to travel regionally (as part of assignment/ training and development or delivery ) in Nepal, India, Pakistan, Bangladesh, or Srilanka
Our Commitments
We believe that diversity drives innovation. At Genese Solution, we are dedicated to creating a work environment where everyone, regardless of race, gender identity, age, religion, disability, or background, feels respected and included.
Interested candidates meeting the above criteria are requested to send their CV and cover letter to hr@genesesolution.com clearly mentioning the position you are applying for in the subject.
NOTE:
- Only shortlisted candidates will be contacted for further selection process.
Finland
Bangladesh