Location: Frisco, TX / Atlanta, GA (Hybrid, locals only)
Duration: 12+ Months
Summary:
• The candidate should be able to serve as the lead technical
contributor for designing and deploying enterprise-grade AI systems.
• This role demands a senior AI engineer who can handle high-level
architectural design and hands-on implementation of complex agentic
workflows.
• The candidate will be responsible for building the “AIObserve”
ecosystem, ensuring that probabilistic AI outputs are translated into
deterministic, secure, and high-value business outcomes.
Responsibilities:
• Architecting Agentic Systems: Design and implement multi-agent systems
using the Model Context Protocol (MCP) to enable seamless tool-calling
across platforms like Atlassian and GitHub.
• Enterprise RAG Implementation: Lead the development of sophisticated Retrieval-Augmented Generation (RAG) layers, integrating vector databases like Milvus with enterprise knowledge bases (Jira/Confluence). • Orchestration & Workflow Automation: Build and optimize backend services using FastAPI and Azure Bot Service to handle real-time message routing and automated ticket fulfillment. • High-Privilege Automation: Develop secure browser automation scripts using Python and Playwright to handle complex tasks such as RBAC validation and post-true-up process automation. • Security & RBAC Engineering: Engineer robust Role-Based Access Control (RBAC) within AI agents to ensure high-privilege operations are executed safely and within compliance.
• Performance Tuning: Optimize system latency to ensure AI responses and
backend acknowledgments meet strict enterprise thresholds (<7 seconds).
• Architecting Observability Pipelines: Design and implement end-to-end
telemetry for AI agents. This includes capturing not just system logs,
but also LLM-specific traces (latency, token usage, and “hallucination”
scores) to provide a 360-degree view of system health
• LLMOps Infrastructure: Own the deployment lifecycle, including CI/CD
for prompt engineering, automated testing of RAG retrieval accuracy, and
monitoring for “model drift” in production.
• Cross-functional Collaboration: Working with product managers, data
scientists, and business stakeholders to translate needs into AI
solutions.
Requirements:
• BS/Advanced degree in quantitative fields: Computer Science, Data
Science, Engineering, Business Analytics, Math/Statistics, or a related
field
• 7+ years of experience in applied AI engineering or related role with
2+ years in agentic development, and/or with a combination of
context/prompt engineering
• Expert-level Python proficiency with emphasis on modular,
object-oriented code, strict typing, and rigorous unit/integration
testing for production
• Experience with building both conversational agents and workflow
agentic processes in production
• Applied experience with multiple LLM stacks/frameworks (e.g., OpenAI,
Claude, Gemini, RAG pipelines), and agent orchestration systems (e.g.,
LangGraph, AutoGen, CrewAI, or LangChain building collaborative
autonomous and complex AI workflows
• Demonstrated comfort with prompt design strategies (chain-of-thought,
few-shot) and context window optimization to ensure high-quality LLM
outputs
• Familiarity with cloud platforms (AWS/Azure), REST APIs, and
containerization (Docker, K8s)
• Experience implementing and managing Vector Databases (e.g., Pinecone,
Milvus, Weaviate) for RAG (Retrieval-Augmented Generation) pipelines.
• Experience with Azure bot services, Fast API, OAuth for API security
is recommended.
• Proficiency in Databricks and SQL (DDL/DML) driving scalable data
architecture and holistically integrating prompt designs, vector
databases, and memory strategies to deliver advanced LLM solutions
• Experience developing and applying state-of-the-art techniques for
optimizing training and inference software to improve hardware
utilization, latency, throughput, and cost
• Passion for staying abreast of the latest AI research and AI systems,
and judiciously applying novel techniques in production
• Excellent communication and presentation skills, with the ability to
articulate complex AI concepts to peers
Awaiting your quick response. Thanks!
P.S. Empower is a top vendor to clients such as Apex Systems LLC,
Sogeti, Randstad, CapGemini, UST and more.
Thanks
Adarsh Sharma
Technical Recruiter | Empower Professionals
Adarsh@empowerprofessionals.com
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