Junior AI Engineer

Cynet Systems•Pittsburgh, PA

7d•Hybrid

About The Position

The Junior AI Engineer is an entry-level role in innovation and platform architecture, focused on creating reference implementations, exploring emerging technology, and helping establish standards and best practices. The engineer contributes to AI engineering and data engineering work alongside experienced engineers and architects, with opportunities to work across Databricks, GCP, and other platforms. The role involves designing, developing, coding, testing, debugging, and documenting applications to meet user-area requirements. Work may include new development as well as supporting, maintaining, and enhancing existing applications. The engineer works with management and stakeholders to identify and specify business requirements, evaluates alternative solutions, and makes recommendations. This position is intended for a candidate with 0–2 years of experience and a strong foundation in Python, data, and AI agents who is ready to develop into a professional engineer. The role is hybrid and based in Pittsburgh, PA. Work is primarily remote, but the successful candidate must live in the Pittsburgh area and attend monthly on-site meetings.

Requirements

Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related discipline.
0–2 years of experience; internships, co-ops, academic projects, and personal projects count toward this experience.
Proficiency in Python.
Understanding of data pipelines, relational data, and modern data stores.
Understanding of how AI agents work, how they are built, and agent architecture, with hands-on agent development experience.
Adept at using generative AI to rapidly understand problems and prototype development work.
Outstanding communication skills; well-spoken, outgoing, and comfortable engaging with technical and business audiences.
Curiosity, aptitude, and drive to learn the technology deeply, write and test code, understand system architecture, and work through the complexity of emerging tools.
Able to work both independently and as part of a team, balance multiple projects, and meet deadlines; able to take direction while working with appropriate self-sufficiency.
Must be based in Pittsburgh, PA, and able to attend monthly on-site meetings.

Nice To Haves

SQL and understanding of relational data.
Exposure to retrieval-augmented generation (RAG), including embeddings, chunking, and vector search.
Exposure to Databricks, GCP, or another cloud data platform.
Experience with natural-language-to-data interfaces.

Responsibilities

Design, build, and deploy AI-enabled applications and agentic workflows that provide business users with grounded answers from enterprise data.
Build and tune retrieval-augmented generation (RAG) solutions, including chunking strategies, embedding generation, and vector search.
Test the accuracy of natural-language generative AI solutions and refine them through prompt and instruction revisions.
Curate source data into retrieval- and agent-ready form, working alongside data engineers on required transformations.
Contribute to data engineering work that supports AI and data solutions.
Collaborate with stakeholders to gather requirements, translate them into technical specifications, and communicate technical concepts to varied audiences.
Assist in evaluating and recommending models, tools, and platforms, and stay current on technology trends.
Create reference implementations, explore emerging technology, and help establish standards and best practices.
Design, develop, code, test, debug, and document applications; support, maintain, or enhance existing applications as needed.
Work closely with management to identify and specify complex business requirements and processes, and research, evaluate, and recommend alternative solutions.