Overview
We are looking for an AI Engineer who approaches technology with a problem-solving mindset first. This role is ideal for someone who can take ambiguous business challenges, think critically, and build practical AI-driven solutions that create measurable impact.
The ideal candidate is hands-on, execution-focused, and comfortable owning solutions end-to-end — from ideation and proof of concept to production deployment. You should be able to effectively leverage modern AI technologies including LLMs, Agentic AI frameworks, APIs, and orchestration tools while collaborating closely with business and engineering stakeholders.
Responsibilities
- Translate ambiguous business problems into clear, scalable, and actionable AI solutions.
- Demonstrate strong critical thinking by evaluating multiple approaches, identifying trade-offs, and making pragmatic decisions.
- Design, build, and deploy end-to-end AI/ML solutions with a strong bias toward execution and ownership.
- Develop and implement Agentic AI solutions using LLMs, APIs, orchestration frameworks, and automation workflows.
- Rapidly prototype, test, and iterate on AI-powered applications and proof-of-concepts.
- Leverage AI tools and frameworks effectively as productivity multipliers while maintaining strong engineering fundamentals.
- Collaborate closely with business stakeholders, product teams, and engineers to deliver measurable business outcomes.
- Ensure production readiness including scalability, reliability, monitoring, and continuous improvement of AI systems.
- Stay updated with emerging AI technologies, frameworks, and industry trends in a fast-moving environment.
Requirements
- 2–3 years of hands-on experience in AI/ML engineering or related software engineering roles.
- Strong understanding of LLMs, Agentic AI architectures, APIs, orchestration frameworks, and modern AI ecosystems.
- Experience building and deploying AI-powered applications or automation solutions in production environments.
- Strong problem-solving and analytical thinking skills with the ability to simplify complex challenges.
- Ability to independently own projects from concept to deployment.
- Comfortable working in fast-paced, evolving environments with continuous learning and experimentation.
- Strong collaboration and communication skills with both technical and non-technical stakeholders.
- Experience with Python and modern AI/ML frameworks and tooling is preferred.
- Familiarity with cloud platforms, vector databases, RAG pipelines, or AI deployment workflows is a plus.