Senior AI Engineer

Responsibilities
Apply an
AI-first mindset when designing and implementing solutions, making use of AI/LLM technologies to improve development efficiency, decision-making, and overall productivity.
Develop, deploy, and scale
AI/ML models to address practical business and product challenges.
Create applications powered by
LLMs
, including chatbots, copilots, AI assistants, and intelligent agents.
Build agent-based solutions that can reason, interact with tools, and handle multi-step tasks.
Design and continuously improve
RAG workflows
, covering embedding, retrieval, and re-ranking to achieve reliable accuracy and performance.
Assess different models and approaches to determine the most suitable architecture for each use case, including LLMs, classification, regression, clustering, recommendation, and related techniques.
Optimize models with a focus on accuracy, response time, and cost efficiency
.
Incorporate AI development tools such as
GPT, GitHub Copilot, Claude
, or similar solutions to automate repetitive workflows and improve engineering productivity.
Implement and maintain
LLM orchestration workflows using frameworks such as LangChain, LangGraph, or equivalent technologies.
Track, assess, and improve AI model performance with tools such as
LangSmith or other comparable solutions.
Work closely with product, backend, and infrastructure teams to bring end-to-end AI solutions into production.
Take ownership of assigned projects or modules and independently drive them from development through delivery.
Stay up to date with emerging AI technologies and identify opportunities to apply them to products and internal processes.
Focus on delivering measurable business and technical outcomes
, such as better accuracy, lower operational costs, or higher automation rates.
Lead or work alongside other engineers on
AI/ML initiatives
, contributing to technical direction, quality standards, and delivery timelines.
Support junior engineers and team members through technical mentoring and guidance.
Contribute to
AI solution architecture and participate in important technical design decisions.
Partner with stakeholders to shape the AI roadmap and convert business requirements into practical technical solutions.
Review code, models, and system designs to maintain engineering standards, scalability, and long-term maintainability.
Requirements
Bachelor's degree in
Computer Science, Artificial Intelligence
, or a related discipline, or equivalent professional experience.
At least
5 years of experience working as an AI Engineer or in a closely related position.
Solid
Python programming skills and familiarity with relevant AI/ML frameworks.
Practical experience developing and deploying
AI/ML solutions in production environments
.
Ability to work independently across the full AI development lifecycle, from research and prototyping through implementation and testing.
Hands-on experience with at least one major cloud platform
, such as AWS, GCP, or Azure.
Experience taking ownership of AI modules/projects or leading and mentoring a small technical team.
Good written and verbal communication skills in
English
.
Nice to have
Practical experience with
RAG solutions and vector databases
, such as Pinecone, Weaviate, or FAISS.
Experience delivering
AI-powered products for real-world use cases, including chatbots, virtual assistants, or intelligent search.
Familiarity with designing APIs and integrating AI capabilities into existing applications.
Strong knowledge of prompt engineering and AI workflow orchestration
.
Ability to study technical/research papers and quickly turn new concepts into prototypes.
Previous experience as a technical lead or ownership of AI solutions running in production.
Experience working across different functions and aligning technical solutions with business and product stakeholders.