Artificial Intelligence Engineer

Contenterra Software; Hyderabad; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Contenterra Software in Hyderabad is seeking a Senior AI Engineer to design and deliver AI-powered capabilities within business applications. You will build reliable reasoning pipelines, intelligent workflows, and agent-driven systems that integrate enterprise data and automate complex processes.

The role requires hands-on experience with RAG, agent workflows, and end-to-end AI feature delivery, plus strong Python skills and familiarity with vector databases, APIs, and cloud deployments.

Qualifications

• 4+ years of hands-on software development building production AI systems.
• Experience delivering end-to-end AI features used by real users.
• Hands-on experience with RAG, agents, or automation workflows.

Responsibilities

• Design AI workflows that execute multi-step business tasks autonomously.
• Build agentic systems capable of planning, reasoning, and actions using tools and APIs.
• Develop multi-agent architectures where specialized agents collaborate to complete processes.
• Implement Retrieval-Augmented Generation (RAG) over enterprise data sources.
• Integrate LLMs via APIs and open-source models using provider-agnostic architecture.
• Design evaluation, guardrails, and validation for reliable AI features.

Skills

Python

LangChain

Agent workflows

Vector databases

API integration

Containerized deployments

Tools

LlamaIndex

DSPy

Semantic Kernel

Job description

Position: AI Engineer

Location: Hyderabad

Employment Type: Full-Time, Permanent

Overview: We are looking for a Senior AI Engineer to design and deliver AI-powered capabilities within business applications. The role focuses on building reliable reasoning pipelines, intelligent workflows, and agent-driven systems that integrate enterprise data and automate complex processes.

Key Responsibilities

• Design AI workflows that execute multi-step business tasks autonomously.
• Build agentic systems capable of planning, reasoning, and taking actions using tools and APIs.
• Develop multi-agent architectures where specialized agents collaborate to complete processes.
• Implement Retrieval-Augmented Generation (RAG) over enterprise data sources.
• Integrate LLMs via APIs and open-source models using provider-agnostic architecture.
• Design structured outputs, guardrails, and validation layers for reliablebehavior.
• Build tool-using AI for database querying, document processing, and API orchestration.
• Create evaluation pipelines to measure accuracy, reliability, and regression of AI outputs.
• Implement observability including tracing, latency, and cost monitoring.
• Design failure handling, fallbacks, and human-in-the-loop workflows.
• Architect scalable async execution using queues and background workers.
• Own production reliability of AI features from deployment through monitoring.
• Evaluate approaches (RAG vs fine-tuning vs workflow vs agents) and justify design decisions.
• Define AI engineering standards and best practices across projects.
• Establish evaluation benchmarks and acceptance criteria for AI features.
• Participate in technical hiring and mentoring of future AI team members.

Experience

• Minimum4+ years software development experience with significant hands-on work building production AI systems.
• Experience delivering end-to-end AI features used by real users.
• Hands-on experience with RAG, agent workflows, or automation systems.

Technical Skills

• Strong Python programming skills.
• Experience with AI frameworks (LangChain,LlamaIndex,DSPy, Semantic Kernel, or similar).
• Understanding of agents, tool calling, and workflow orchestration patterns.
• Experience with vector databases and retrieval systems.
• Knowledge of evaluation methodologies for AI outputs.
• Experience integrating AI systems with APIs, databases, and backend applications.
• Familiarity with containerized deployments and cloud platforms.

Good to Have

• Experience with multi-agent coordination patterns.
• LLMOpspractices (versioning, rollback, evaluation datasets).
• Working withopen-source/local models.
• Security and safety considerations in AI systems.
• Experience improving business workflows using AI automation.

Soft Skills

• Ability to work with ambiguous requirements and drive solution design.
• Strong debugging ability in non-deterministic systems.
• Clear communication and technical ownership.