Senior AI Engineer
Argano (company site, opens in a new tab)HyderabadRemoteDirect career pageEst. 30–55 LPA
Posted 1d ago
Reach people at Argano
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Argano you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Work with clients to map business workflows in areas such as finance, customer service, or supply chain, then identify automation opportunities.
- Design, build, and deploy enterprise AI agents and RAG solutions on Azure, including Azure AI Foundry; own delivery from requirements through production rollout and support.
- Integrate AI into client systems and monitor agent quality, safety, cost, and performance using enterprise software and DevOps practices.
Minimum Requirements
- Work Experience Required: Not explicitly mentioned in the JD. Proven client-facing experience and experience delivering enterprise implementations are required.
- Hands-on experience building AI agents on Azure, including Azure AI Foundry, and RAG solutions using retrieval techniques; working knowledge of agent runtime, orchestration, models, and tooling.
- Software development experience across microservice and monolithic architectures; proficiency in C# and Python, plus DevOps practices including CI/CD, infrastructure as code, and observability.
- Experience with Azure and at least one additional major cloud platform (AWS or Google Cloud); business process or workflow analysis in at least one relevant domain. Role is based in Mexico or Colombia.
Ideal Candidate Profile
- Can translate client business workflows into practical AI automation, and communicate technical decisions to both technical and non-technical stakeholders.
- Has delivered enterprise AI solutions end to end, balancing agent and retrieval design with integration into existing systems and production operations.
- Offers broad implementation experience across programming languages, architectures, and cloud platforms; agent frameworks, vector search, LLM evaluation, responsible AI, or enterprise security experience are preferred.