We are looking for a Hands-On Agentic AI Engineer to join a new team focused on applying AI agents and intelligent workflows to improve business processes across the organization.
The ideal candidate is someone who enjoys building real-world AI-driven solutions end-to-end – writing code, designing architectures, building prototypes, solving implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI solutions.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data – validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
Governance, Reliability & Security
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners and IS teams to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations.
The ideal candidate is someone who enjoys building real-world AI-driven solutions end-to-end – writing code, designing architectures, building prototypes, solving implementation challenges, and working directly with business stakeholders to turn process opportunities into working AI solutions.
Responsibilities:
Partner directly with business teams to identify automation and optimization opportunities
Design and implement agent-based AI workflows to automate internal processes end-to-end
Design and build LLM-powered tools (agents, workflows, copilots)
Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows
Deep-dive into company data – validate quality, uncover gaps, and ensure AI solutions are built on solid foundations
Take solutions from idea → prototype → production
Governance, Reliability & Security
Ensure AI workflows comply with security, privacy, and compliance requirements
Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed
Monitor AI performance, errors, hallucinations, and drift
Collaboration & Enablement:
Partner with business owners and IS teams to identify automation opportunities
Translate business requirements into AI-driven solutions
Document AI flows, decision logic, and operational runbooks
Educate internal teams on AI capabilities and limitations.
Requirements:
2-3 years of proven experience with AI solutions
Strong hands-on software development experience, including writing, maintaining, and delivering production-quality code
Strong GenAI development experience with LLMs, SLMs, prompt engineering, context engineering, and agent-based systems
Strong Python skills and a production-focused engineering mindset
Experience designing and building agentic AI workflows, RAG pipelines, LLM-powered applications, copilots, or intelligent automation solutions
Experience bringing AI agents, GenAI applications, or automation solutions into production
Solid understanding of APIs, integrations, databases, cloud environments, monitoring, logging, security, and deployment practices
Ability to work directly with non-technical stakeholders and translate business needs into technical solutions
Experience with AWS AgentCore, n8n, UiPath, Make, Workato, or similar is an advantage
Experience with enterprise AI governance, security, compliance, and privacy requirements is an advantage
Strong builder mindset: proactive, independent, hands-on, business-oriented, and impact-driven.
2-3 years of proven experience with AI solutions
Strong hands-on software development experience, including writing, maintaining, and delivering production-quality code
Strong GenAI development experience with LLMs, SLMs, prompt engineering, context engineering, and agent-based systems
Strong Python skills and a production-focused engineering mindset
Experience designing and building agentic AI workflows, RAG pipelines, LLM-powered applications, copilots, or intelligent automation solutions
Experience bringing AI agents, GenAI applications, or automation solutions into production
Solid understanding of APIs, integrations, databases, cloud environments, monitoring, logging, security, and deployment practices
Ability to work directly with non-technical stakeholders and translate business needs into technical solutions
Experience with AWS AgentCore, n8n, UiPath, Make, Workato, or similar is an advantage
Experience with enterprise AI governance, security, compliance, and privacy requirements is an advantage
Strong builder mindset: proactive, independent, hands-on, business-oriented, and impact-driven.
This position is open to all candidates.
