Artificial Intelligence Engineer

AI Engineer

About the Role :

We're looking for an AI Engineer to design, build, and operate agentic AI systems for enterprise clients from prompt design through deployment, evaluation, and ongoing monitoring.

What You'll Do

• Build and enhance LLM-powered applications and agentic AI solutions. • Develop AI agents, multi-agent workflows, RAG solutions, and tool integrations.

• Work with AWS AI/ML services to develop and deploy AI solutions.

• Implement evaluation, monitoring, and observability for AI systems.

• Collaborate with teams to translate business requirements into practical AI solutions.

Required Skills :

1. Python & Software Engineering

o Strong hands-on experience with Python (3.11+)

o Familiarity with asynchronous programming, type safety, testing, APIs

2. Generative AI & Agentic AI

o Experience building applications using LLMs

o Have overall understanding in Prompt and context engineering

o Multi-agent orchestration using LangGraph, CrewAI, AutoGen, or any agentic orchestration framework.

o Tool management and discovery, including tool integration, selection, registration, and lifecycle management

o Model Context Protocol (MCP) or similar approaches for connecting agents with external systems

3. RAG & Knowledge Systems

o Experience with Retrieval-Augmented Generation (RAG)

o Familiarity with chunking and its techniques, embeddings, vector stores, retrieval, reranking, and evaluation methodologies.

o Familiarity with Open Knowledge Formats and structured knowledge representation

.

4. AWS AI/ML Services

o Experience or familiarity with AWS Bedrock and AgentCore capabilities Agent Runtime

Memory

Identity

Tool Gateway

o Experience or familiarity with AWS SageMaker

Model training and deployment

Endpoint management

Model registry

5. Machine Learning & Data Science

o Experience with ML frameworks such as scikit-learn, TensorFlow, PyTorch, or equivalent.

o Exploratory Data Analysis (EDA), data preprocessing, visualization, and feature engineering

o Familiarity with Pandas, NumPy, Matplotlib/Seaborn, or equivalent tools

o Able to perform EDA using Dataiku

6. MLOps, Evaluation & Observability

o Understanding of ML model lifecycle, evaluation, monitoring, and production workflows

o Experience or familiarity with agent evaluation and observability

Agent/workflow tracing

Tool usage and response evaluation

Quality and groundedness evaluation

Latency and cost monitoring

Failure analysis and regression testing

o Familiarity with tools such as LangSmith, MLflow, OpenTelemetry, or equivalent

7. AI Security, Performance & Governance

o Understanding of AI/agent security and governance

o Access control, tool permissions, guardrails, prompt-injection protection, and data security

o Familiarity with performance, scalability, latency, and AI cost optimization

8. DevOps & Cloud Engineering

o Familiarity with CI/CD and DevOps practices

o Experience integrating AI/ML applications with enterprise systems and cloud infrastructure

Nice to Have

• At least one relevant AWS certification is preferred, Solutions Architect Associate, Developer Associate, AI Practitioner, or equivalent

• Experience fine-tuning open-source models (e.g. Qwen, Llama)

• A published open-source AI project, package, or meaningful contribution to an agentic AI framework or project

• Familiarity with AI coding assistants (Claude Code, GitHub Copilot) as part of your own workflow

Soft Skills We Value

• Having strong communication skills and the ability to clearly understand and explain technical concepts, ideas, and their alignment with business needs.

• Strong written communication documenting architecture decisions and explaining AI systems

• Self-directed able to invest time in themselves and adapt to learn emerging AI technologies, frameworks, and evolving cloud services in a fast-moving environment