AI Engineer - 504

Johnson Service Group

Dallas, TX

Apply

JOB DETAILS

SKILLS

AWS Lambda, Algorithms, Amazon Simple Storage Service (S3), Amazon Web Services (AWS), Analysis Skills, Application Programming Interface (API), Architectural Analysis, Artificial Intelligence (AI), C Programming Language, C++ Programming Language, Caching, Circuit Breakers, Cloud Computing, Communication Skills, Cost Control, Data Management, Data Processing, Data Quality, Data Structures, Ecosystems, Experiment Design, Go Programming Language (Golang), Incident Management, Java, MCP - Microsoft Certified Professional, Mentoring, Model Validation, Modeling Languages, Open Source, Performance Tuning/Optimization, Problem Solving Skills, Production Systems, Python Programming/Scripting Language, Quality Engineering, Risk, Risk Management, Safety Compliance, Safety Engineering, Sales Pipeline, Software Development, Statistics, Test Design, Traceability

LOCATION

Dallas, TX

POSTED

30+ days ago

Must Haves:

5+ years of software development in one or more languages (Python, C/C++, Go, Java); strong hands-on experience building and maintaining large-scale Python applications preferred.
3+ years designing, architecting, testing, and launching production ML systems, including model deployment/serving, evaluation and monitoring, data processing pipelines, and model fine-tuning workflows.
Practical experience with Large Language Models (LLMs): API integration, prompt engineering, fine-tuning/adaptation, and building applications using RAG and tool-using agents (vector retrieval, function calling, secure tool execution).
Understanding of different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude).
Solid grasp of applied statistics, core ML concepts, algorithms, and data structures to deliver efficient and reliable solutions.
Strong analytical problem-solving, ownership, and urgency; ability to communicate complex ideas simply and collaborate effectively across global teams with a focus on measurable business impact.

Nice to Haves:

Proficiency building and operating on cloud infrastructure (ideally AWS), including containerized services (ECS/EKS), serverless (Lambda), data services (S3, DynamoDB, Redshift), orchestration (Step Functions), model serving (SageMaker), and infra-as-code (Terraform/CloudFormation).

Responsibilities:

Build agentic AI systems: Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol. Engineer robust guardrails for safety, compliance, and least-privilege access.
Productionize LLMs: Build evaluation framework for open-source and foundational LLMs; implement retrieval pipelines, prompt synthesis, response validation, and self-correction loops tailored to production operations.
Integrate with runtime ecosystems: Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post-incident summarization with full traceability.
Collaborate directly with users: Partner with production engineers, and application teams to translate production pain points into agentic AI roadmaps; define objective functions linked to reliability, risk reduction, and cost; and deliver auditable, business-aligned outcomes.
Safety, reliability, and governance: Build validator models, adversarial prompts, and policy checks into the stack; enforce deterministic fallbacks, circuit breakers, and rollback strategies; instrument continuous evaluations for usefulness, correctness, and risk.
Scale and performance: Optimize cost and latency via prompt engineering, context management, caching, model routing, and distillation; leverage batching, streaming, and parallel tool-calls to meet stringent SLOs under real-world load.
Build a RAG pipeline: Curate domain-knowledge; build data-quality validation framework; establish feedback loops and milestone framework maintain knowledge freshness.
Raise the bar: Drive design reviews, experiment rigor, and high-quality engineering practices; mentor peers on agent architectures, evaluation methodologies, and safe deployment patterns

#LI-TF1

About the Company

Johnson Service Group

At JSG, We Understand People

It is our mission to empower people, help our clients reach their goals, and hire motivated individuals.

Since our start in 1984, we’ve worked hard to establish our present position as the most effective cross-industry staffing and consulting solution available.

Headquartered in Chicago, IL with local offices throughout the United States and Canada, JSG proudly serves a diverse range of industries with the right solutions to help clients reach their company goals. Our client-centric approach enables us to create personalized solutions for businesses in need of top-tier talent. Our dedication doesn’t stop at our clients. We strive to connect candidates with opportunities that match their skills and goals. More than just a go-between, we are a dependable bridge, uniting top talent with suitable opportunities, facilitating shared opportunities and growth.

COMPANY SIZE

1,000 to 1,499 employees

INDUSTRY

Staffing/Employment Agencies

FOUNDED

1984

WEBSITE

https://www.jsginc.com/

Resume Resources

Free Resume Templates Free Resume Builder