AI Engineer
Insight Global
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.
Required Skills & Experience 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 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.
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.
$200k - $300k
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$114k - $148k
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$110k - $130k
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$79.31k - $158.62k
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$90k - $150k
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$112.9k - $160.5k
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