AI Engineer/Architect
VLink Inc.
Job Description
Job Title: AI Engineer/Architect
\nLocation: Lafayette, LA | Hybrid
\nEmployment Type: Contract
\nDuration: 6-12 months
\n \nAbout:
\nVLink, founded in 2006, is a leading global provider of software engineering services with next-gen technologies and best-in-class talent. Our Headquarters are in the U.S, and we have offices in 7+ countries from North America-Europe to APAC, with expansion plans in the Middle East. With over 1,000 employees working globally, VLink has helped SMBs, and large enterprises achieve their business goals, and gained the trust of Fortune-250 companies. VLink is 'Great Place to Work® Certified™' and has been a consistent winner as- Best Places to Work in CT. Trust, collaboration, and accountability are the three elements that are at the core of VLink's work culture. We value our professionals, providing comprehensive benefits and the opportunity for growth.
\n \nJob Details:
\nOur client is seeking a highly skilled and experienced Senior AI Engineer to join their Health Care client in one of our selected client locations. This is an exciting opportunity to work in a fast paced team environment supporting one of the largest leaders in the Health Care industry.
\nThis Senior AI Engineer will be instrumental to design, develop, and lead enterprise grade Generative AI solutions. This role requires deep hands on expertise in Python, Large Language Models (LLMs), prompt engineering, embeddings, vector databases, and agent based architectures.
\nThe role will work closely with the AI Center of Excellence (AI CoE) to ensure alignment with enterprise AI standards, governance, and best practices while driving adoption across delivery teams.
\nAs an AI Architect, you will shape reusable architecture patterns for multi agent orchestration, Model Context Protocol (MCP) tool ecosystems, AI powered conversational experiences, and high performance backend services.
\nThe position combines hands on technical leadership with enterprise architecture influence, giving you the opportunity to mentor teams and guide AI solutions from concept through production adoption.
\n \nYour future duties and responsibilities:
\nThe AI Architect will own the architecture and technical direction for enterprise agentic AI solutions, balancing hands on engineering with design governance. The role will establish reusable patterns for multi agent orchestration, MCP enabled tool ecosystems, secure backend services, integration, observability, and production reliability.
\n \nAI Architecture & Multi Agent Orchestration
\n- \n
- Architect and implement robust multi agent orchestration using Python and LangGraph, including intelligent routing, dynamic handoffs, shared state management, long term memory, tool calling, error recovery, and follow up conversation flows. \n
- Define target and reference architectures for agentic AI, retrieval augmented generation (RAG), model access, memory, evaluation, and human in the loop controls. \n
- Establish reusable architecture patterns, engineering standards, guardrails, and design review practices for enterprise AI solutions. \n
MCP & Agent Ecosystem
\n- \n
- Design, develop, and maintain MCP servers using FastAPI and Python to expose tools, resources, prompts, and custom capabilities as part of the agent ecosystem. \n
- Define standards for tool contracts, discovery, versioning, permissions, schema validation, error handling, and safe execution. \n
- Build and maintain custom tools and integrations that connect AI agents with internal APIs, enterprise data sources, and legacy systems. \n
AI Powered Products & Domain Solutions
\n- \n
- Design complex AI powered chatbots and insights engines for critical healthcare and pharmacy benefit management workflows, including claims, pharmacy search, drug coverage, and prior authorization. \n
- Translate business and product requirements into scalable technical designs and guide solutions from proof of concept through production implementation. \n
- Select appropriate model, RAG, memory, orchestration, and tool use patterns based on quality, latency, cost, security, and compliance requirements. \n
Backend Services, Integration & Security
\n- \n
- Own the architecture and development of high performance FastAPI services, including streaming responses, asynchronous processing, custom middleware, rate limiting, caching, and authentication and authorization strategies. \n
- Design resilient integration patterns for APIs and legacy platforms, including retries, idempotency, timeouts, circuit breakers, fallbacks, and auditability. \n
- Ensure solutions follow security, privacy, responsible AI, secrets management, input/output validation, and regulated data handling best practices. \n
Observability, Reliability & Optimization
\n- \n
- Implement comprehensive observability using LangSmith, distributed tracing, monitoring, logging, evaluation, error handling, and performance tuning for AI agent workloads. \n
- Define service level objectives and quality measures for latency, answer quality, tool accuracy, task completion rate, reliability, and cost. \n
- Identify and prioritize technical improvements in agent performance, latency, tool accuracy, scalability, and overall system architecture. \n
Technical Leadership & Collaboration
\n- \n
- Collaborate cross functionally with frontend, DevOps, product, security, data, and enterprise architecture teams to deliver end to end AI capabilities with high reliability. \n
- Lead architecture reviews, mentor developers, communicate design trade offs, and establish implementation guidance for distributed delivery teams. \n
- Evaluate emerging AI technologies pragmatically and recommend adoption based on measurable business value and enterprise readiness.Required qualifications to be successful in this role \n
Essential Qualifications
\n- \n
- 12+ years of professional software engineering and solution architecture experience, including hands on delivery of enterprise applications and platforms. \n
- 5+ years of AI/ML experience with recent hands on delivery of production Generative AI and agentic AI solutions. \n
- Expert level Python skills and strong experience designing scalable, secure, production grade backend services using FastAPI. \n
- Hands on experience with LangGraph or a comparable framework for multi agent orchestration, including routing, handoffs, shared state, memory, tool use, recovery, and conversational continuity. \n
- Experience designing and implementing MCP servers and governing tools, resources, prompts, schemas, permissions, and lifecycle management within an agent ecosystem. \n
- Deep understanding of LLMs, prompt engineering, RAG, embeddings, vector search, memory patterns, function/tool calling, model evaluation, and guardrails. \n
- Proven experience designing AI powered chatbots, insights engines, or workflow automation solutions that integrate with enterprise APIs, data sources, and legacy systems. \n
- Strong knowledge of API and distributed system patterns, including streaming, asynchronous processing, middleware, rate limiting, authentication, authorization, resilience, and observability. \n
- Experience implementing LangSmith or equivalent AI observability, tracing, evaluation, debugging, and performance monitoring capabilities.]Strong understanding of cloud native architecture, containers, CI/CD, security, privacy, responsible AI, and operational support for regulated enterprise workloads. \n
- Demonstrated ability to lead architecture decisions, mentor engineering teams, facilitate design reviews, and communicate complex trade offs to technical and business stakeholders. \n
Expectations:
\n- \n
- Own solution architecture end to end, from discovery and design through implementation, production readiness, and adoption. \n
- Balance innovation with reliability, security, cost, maintainability, and measurable business outcomes. \n
- Drive architectural simplification, reuse, and consistent engineering practices across AI implementations. \n
- Operate as a hands on technical leader who can validate critical designs and implementation patterns through working code and prototypes. \n
- Build trusted partnerships across product, engineering, DevOps, security, data, and enterprise architecture teams. \n
Employment Practices:
\nVLink is an equal opportunity employer committed to fostering an inclusive environment where diversity is celebrated. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. Employment is contingent upon successful completion of a background check.
\n \nThis job application process may use AI-powered tools to assist in screening and evaluating applications based on objective, job-related qualifications. AI is used solely to support the recruitment process and all final hiring decisions are made exclusively by our human recruitment team.
\n \nApplicant information will be handled in accordance with VLink's privacy policy.
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