AI/ML Engineer

Job Description

We're looking for **AI/ML Engineers!**

**Responsibilities:**

* Support development of Python-led AI/ML components, scripts and AI pipeline utilities under guidance from senior engineers.
* Assist in prompt engineering, structured output testing, basic RAG implementation, and validation of LLM responses.
* Participate in API testing, integration validation, documentation, and defect resolution activities.
* Contribute to unit testing, AI output checks, data preparation, debugging, and deployment support.
* Build foundational understanding of Agentic AI workflows, tool calling, orchestration and enterprise integration patterns.

**Must Have Skills**

· **Python \& Full-Stack Development**

· **Agentic AI (LangChain, LangGraph, MCP, RAG)**

· Good Python programming fundamentals including scripting, data structures and Object-Oriented Programming concepts.

· Basic exposure to AI/ML concepts, GenAI, prompt engineering or LLM-enabled applications.

· Understanding of REST APIs, JSON, Git and software development lifecycle basics.

· Ability to write clean code, test outputs, document work, and learn fast in a POD-based delivery model.

**Secondary Skills**

· Exposure to RAG, vector databases, LangChain, LangGraph, Semantic Kernel or CrewAI is preferred.

· Basic understanding of cloud platforms, Docker, CI/CD, testing and observability concepts.

· Interest in responsible AI, AI guardrails, enterprise integration and production-readiness practices.

**Skill Area**

**Skill Requirement**

**Addl Notes**

**Agentic AI Concepts**

Deep understanding of AI agent design, reasoning loops, orchestration patterns \& multi-agent coordination architectures

Core differentiator; senior levels lead architecture design

**Agentic AI Concepts**

Tool calling, function routing, agent memory \& state management, autonomous decision-making patterns

Applicable across levels; depth scales with seniority

**LLM \& Prompt Engineering**

Hands-on with LLMs (GPT-4, Claude, Gemini); prompt engineering, few-shot, chain-of-thought \& structured output techniques

Focus on prompt craft

**LLM \& Prompt Engineering**

RAG pipeline design, vector database integration (Pinecone, Weaviate, ChromaDB) \& semantic search for enterprise grounding

RAG critical for enterprise-grade AI accuracy

**AI Frameworks**

Exposure in LangGraph, LangChain, Semantic Kernel or CrewAI for production-grade agentic workflow development

**Programming \& APIs**

Strong Python skills --- async programming, OOP, data structures \& scripting for AI pipelines; Java/.NET acceptable

Python strongly preferred for AI workloads

**Programming \& APIs**

REST/GraphQL API development, microservices design \& enterprise application integration patterns

Integration skills essential for enterprise deployment

**Cloud \& DevOps**

Azure / AWS / GCP hands-on experience; cloud-native architecture, infrastructure provisioning \& managed AI services

AWS preferred for this engagement; cloud-agnostic skills valued

**Cloud \& DevOps**

Containerization (Docker, Kubernetes), CI/CD pipeline setup, GitOps \& automated deployment practices

CI/CD mandatory

**Security \& Responsible AI**

Security principles, identity management (OAuth, Azure AD), AI guardrails, bias mitigation \& enterprise compliance

**Enterprise Integration**

Integrating with enterprise platforms: ServiceNow, Appian, SAP, Salesforce \& Microsoft ecosystem (M365, Teams, Power Platform)

Platform experience maps directly to client landscape

**Testing \& Observability**

AI solution testing, LLM output evaluation, observability (tracing, monitoring), performance tuning \& cost optimization

Observability critical for production AI agents

(**\*Note:**Scoutit is an independent candidate sourcing partner for this hiring. All applications, candidate screening, and hiring-related actions are conducted directly by the respective employer's authorized recruitment team. Relevant candidates will be contacted via email and asked to fill in additional details as part of the next stage of the application process.)