What You will do (Responsibilities) :

• Design, build, and deploy AI agents and AI-enabled services.
  ● Translate business workflows into automated and AI-assisted systems.
  ● Integrate LLMs with internal platforms, APIs, and data sources.
  ● Start with rules and automation. Add AI only where it adds clear value.
  ● Develop AI services using Python and modern backend frameworks.
  ● Own model quality, evaluation, versioning, and observability.
  ● Design feedback loops to continuously improve AI output quality.
  ● Define accuracy targets, confidence thresholds, and human review paths.
  ● Monitor production systems for failures, drift, and edge cases.
  ● Optimize inference cost, latency, and reliability.
  ● Instrument systems to measure usage, accuracy, and operational impact.
  ● Collaborate with ML Engineers and Data teams where model training or data pipelines are required.
  ● Ensure AI systems comply with PDPL, security, and responsible AI practices.
  ● Design explainable AI behaviors and human-in-the-loop workflows to build trust.
  ● Work closely with Finance, Operations, Sales, and other teams.
  ● Document system behavior, trade-offs, and limitations clearly.
  ● Apply AI tools to improve software delivery efficiency, quality, and reliability where there is clear impact.
  ● Partner with Engineering to evaluate and apply targeted AI-assisted tooling across the SDLC.

Who You are (Qualifications) : 

● 5+ years in applied AI or AI engineering roles.
● Bachelor’s degree in Computer Science or a related field.
● Strong Python skills with production backend experience.
● Hands-on experience with LLMs, prompt design, and agent frameworks.
● Experience with vector databases and retrieval systems.
● Experience evaluating AI outputs and improving accuracy over time.
● Experience deploying AI services on cloud platforms.
● Strong data handling and debugging skills.
● Experience integrating APIs and internal systems.

Skills & Competencies Required: 

● Python and FastAPI.
● LLMs, prompt engineering, and agent orchestration.
● Vector databases such as Pinecone or equivalents.
● Model evaluation and quality monitoring.
● Workflow automation tools such as n8n or similar.
● API design and system integration.
● PostgreSQL and basic data modeling.
● GitHub, Docker, and Terraform.
● Basic GCP or AWS services for deployment and monitoring.
● Understanding of security, PDPL, and responsible AI handling.

What we offer:

• It is an excellent opportunity to be part of a start-up with a lot of responsibility and independence early on and where you will impact the entire business.
• Attractive compensation package
• Access to tools helping with your learning and development
• Product first mindset
• The best idea wins; we are all ears about ways to do things better.
• Exciting stock options