AI Engineer

Job Description

Front-End

Proficiency in Angular or equivalent component libraries.

Back-End

Working knowledge of Java (Java 21+) and Spring Boot (REST APIs, Spring Data JPA, Spring Security basics).

Familiarity with Oracle Database: SQL, joins, indexing, and stored procedures; experience with JPA/Hibernate entity mapping.

Understands RESTful API design principles and can document APIs using OpenAPI/Swagger.

Python & AI/ML

Solid Python proficiency: familiarity with async/await, type hints, virtual environments, and packaging.

Hands-on experience with at least one LLM orchestration framework (LangChain, LangGraph, LlamaIndex, or equivalent).

Experience consuming LLM APIs (OpenAI, Azure OpenAI, Anthropic, Cohere, etc.) and working with prompt engineering best practices.

Exposure to agentic AI concepts: tool-calling, function calling, ReAct patterns, RAG, vector stores.

Familiarity with FastAPI or similar Python API frameworks for serving AI pipelines.

Analytical & Problem Solving

Demonstrated ability to break down ambiguous business problems into technical requirements.

Strong debugging and troubleshooting instincts across multiple layers of a system.

Comfort reading and interpreting SOPs, business process documents, and workflow diagrams.

General

Familiarity with Git, CI/CD basics, Docker, and working in a team-based agile environment.

Ability to communicate technical concepts to non-technical stakeholders clearly.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Front-End

Proficiency in Angular or equivalent component libraries.

Back-End

Working knowledge of Java (Java 21+) and Spring Boot (REST APIs, Spring Data JPA, Spring Security basics).

Familiarity with Oracle Database: SQL, joins, indexing, and stored procedures; experience with JPA/Hibernate entity mapping.

Understands RESTful API design principles and can document APIs using OpenAPI/Swagger.

Python & AI/ML

Solid Python proficiency: familiarity with async/await, type hints, virtual environments, and packaging.

Hands-on experience with at least one LLM orchestration framework (LangChain, LangGraph, LlamaIndex, or equivalent).

Experience consuming LLM APIs (OpenAI, Azure OpenAI, Anthropic, Cohere, etc.) and working with prompt engineering best practices.

Exposure to agentic AI concepts: tool-calling, function calling, ReAct patterns, RAG, vector stores.

Familiarity with FastAPI or similar Python API frameworks for serving AI pipelines.

Analytical & Problem Solving

Demonstrated ability to break down ambiguous business problems into technical requirements.

Strong debugging and troubleshooting instincts across multiple layers of a system.

Comfort reading and interpreting SOPs, business process documents, and workflow diagrams.

General

Familiarity with Git, CI/CD basics, Docker, and working in a team-based agile environment.

Ability to communicate technical concepts to non-technical stakeholders clearly. Nice-to-Have Skills

Experience with LangGraph specifically (stateful multi-agent graphs, conditional routing, checkpointing).

Exposure to enterprise integrations: ServiceNow, LDAP/AD, Microsoft Graph API, JIRA, or similar.

Exposure to observability tools: logging, tracing (LangSmith, OpenTelemetry), and metrics.

Familiarity with prompt testing frameworks or evals for LLM quality assurance.