AI Engineer

Xactus•Broomall, PA

5d•Remote

About The Position

The AI Engineer (GenAI Features) specializes in designing, building, and deploying production-grade generative AI applications. This role focuses on translating GenAI concepts into customer-facing and internal features using modern LLM frameworks (LangChain, LangSmith, Agentcore) and advanced retrieval architectures (RAG, GraphRAG with Neo4j/Neptune). The AI Engineer collaborates closely with DevOps and data engineering teams to architect end-to-end solutions, write custom ETL logic, and optimize retrieval systems. Success requires deep expertise in GenAI patterns, knowledge graph design, semantic search, and the ability to bridge research and production while maintaining code quality and system reliability.

Requirements

Bachelor’s degree in related field or equivalent 3–5 years building production AI/ML systems or full-stack applications.
Experience with ML/AI frameworks (PyTorch, TensorFlow, scikit-learn).
1–2+ years with LangChain, LangSmith, or similar LLM frameworks.
Hands-on experience with Claude and/or GPT models.
2+ years of AWS experience (S3, CloudFormation, CloudWatch).
Strong Python and FastAPI.
SQL expertise.
RAG and semantic search experience.
Software engineering discipline (testing, code review, CI/CD).
Strong written and verbal communication skills
Deep understanding of Claude, GPT, and Codex capabilities, limitations, and failure modes.
Breaks complex AI problems into components; designs experiments to validate strategies.
Builds for failure, monitors proactively, responds rapidly to production issues.
Communicates effectively with DevOps, data engineers, and product teams.
Candidates must be a resident of the United States, and should be authorized and eligible for employment in the United States.
Employment is contingent upon successful completion of required background checks (including but not limited to federal and state criminal history checks, employment history verification, education verification, credit history check) and pre-employment drug screening.

Nice To Haves

AWS Bedrock
Codex/code generation models
Prompt engineering at scale
GraphRAG/Neo4j/Neptune
Deep learning (CNNs, RNNs, transformers)
NLP (tokenization, embeddings, text classification)
Hyperparameter optimization
Computer vision/OCR
Terraform
Docker/Kubernetes
MLflow
OpenSearch
AWS Glue
Track record of shipping GenAI features.

Responsibilities

Build production GenAI applications using LangChain, LangSmith, and Agentcore.
Implement complex agent workflows with tool use, memory management, and multi-step reasoning.
Design and optimize agentic patterns for reliability, latency, and cost.
Design and implement retrieval-augmented generation systems using semantic search and vector databases.
Architect knowledge graphs using Neo4j/Neptune for structured reasoning.
Optimize retrieval strategies for accuracy, latency, and relevance ranking.
Write custom Python ETL scripts for data preparation, indexing, and synchronization.
Design schema and data models for graph databases.
Collaborate with data team on AWS Glue orchestration and S3 management.
Write optimized SQL queries and design database schema.
Optimize Neo4j/Neptune Cypher/SPARQL queries and implement efficient vector similarity search in OpenSearch.
Build production FastAPI services for GenAI features.
Implement async request handling, error management, and fallback strategies for LLM unreliability.
Establish experiment tracking using MLflow, including model versioning, hyperparameter logging, and metrics comparison.
Log and monitor LLM outputs for quality and bias.
Implement logging, metrics, and tracing using CloudWatch and LangSmith.
Monitor LLM latency, token usage, and costs.
Respond to production incidents with rapid remediation.
Write unit, integration, and end-to-end tests.
Perform code reviews and test AI system outputs for correctness and safety.
Partner with DevOps to deploy GenAI services.
Communicate with data engineering on pipeline needs.
Work with product to translate requirements into technical designs.
Document system architectures, RAG/GraphRAG designs, and operational runbooks.
Share learnings on agent patterns and prompt engineering.

Benefits

medical, vision and dental insurances
bonus programs
fitness reimbursement and other healthy life-style programs through our benefits carrier
401k plan with a company match
short and long-term disability
life insurance
accident and critical illness insurance
health savings account
flexible spending account
employee assistance program
legal services
employee discounts