ai engineer

Tata Consultancy Services (TCS)

<div></div><div><div><div><div><div>Job Summary: We are seeking a motivated and talented AI Engineer to join our dynamic team. The ideal candidate will have 2-3 years of hands-on experience in developing and implementing AI solutions. You will work on exciting projects involving Large Language Models (LLMs) and help us build the next generation of intelligent products. This role is perfect for a passionate engineer who is eager to apply their skills to solve real-world problems and grow their career in the field of Artificial Intelligence.
</div><div>Key Responsibilities:
</div><div>Develop, train, and deploy machine learning models, with a focus on Large Language Models (LLMs).
</div><div>Collaborate with senior engineers and data scientists to build and integrate AI features into new and existing products.
</div><div>Assist in fine-tuning and optimizing AI models for performance, speed, and cost-effectiveness.
</div><div>Work with large datasets to prepare and process data for training and evaluation.
</div><div>Implement and maintain AI development and production pipelines.
</div><div>Stay up-to-date with emerging trends and technologies in AI and machine learning.
</div><div>Contribute to the entire lifecycle of AI projects, from conception and experimentation to deployment and monitoring.</div><div><br>
</div><div></div><br>
<div>Salary Range: $80,000-$100,000 a year</div><br>
<div><br>
</div><div>TCS Employee Benefits Summary:
</div><div>Discretionary Annual Incentive.
</div><div>Comprehensive Medical Coverage: Medical &amp; Health, Dental &amp; Vision, Disability Planning &amp; Insurance, Pet Insurance Plans.
</div><div>Family Support: Maternal &amp; Parental Leaves.
</div><div>Insurance Options: Auto &amp; Home Insurance, Identity Theft Protection.
</div><div>Convenience &amp; Professional Growth: Commuter Benefits &amp; Certification &amp; amp; Training Reimbursement.
</div><div>Time Off: Vacation, Time Off, Sick Leave &amp; Holidays.
</div><div>Legal &amp; Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.</div><br>
<div><br>
</div><div>#LI-DNI</div><br>
<div><br>
</div></div></div></div><div><div><div><b>Location</b></div>
<div>Edison, NJ</div>
</div><div><div><b>Job Function</b></div>
<div>TECHNOLOGY</div>
</div><div><div><b>Role</b></div>
<div>Engineer</div>
</div><div><div><b>Job Id</b></div>
<div>415384</div>
</div><div><div><b>Desired Skills</b></div>
<div>Artificial Intelligence</div>
</div><div><div><b>Salary Range</b></div>
<div>$100,000-$120,000 a year</div>
</div></div><p>Desired Candidate Profile
</p><div><div><b>Qualifications</b> : BACHELOR OF COMPUTER SCIENCE</div></div></div><div></div>

AI Engineer

BlackStone eIT

<div>
 BlackStone eIT is looking for a skilled AI Engineer to join our innovative team. As an AI Engineer, you will design, develop, and implement artificial intelligence solutions that address complex business challenges. You will work closely with data scientists, engineers, and stakeholders to build scalable AI models and integrate them into product offerings.
 <br/>
 <br/>
 This position offers a great opportunity to contribute to cutting-edge AI projects and help drive the adoption of AI technologies within our organization. You will be involved in all stages of AI project development, from data collection and preprocessing to model training, deployment, and monitoring.
 <br/>
 <br/>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3+ years of experience in AI or machine learning engineering roles
  </li>
  <li>
   Proficiency in programming languages such as Python and experience with AI/ML libraries like TensorFlow, PyTorch, or Scikit-learn
  </li>
  <li>
   Knowledge of AI model deployment and monitoring best practices
  </li>
  <li>
   Understanding of data processing, feature engineering, and model evaluation techniques
  </li>
  <li>
   Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or a related field
  </li>
  <li>
   Strong problem-solving abilities and excellent communication skills
  </li>
  <li>
   Experience with cloud computing platforms (AWS, Azure, or GCP) is preferred
  </li>
  <li>
   Familiarity with containerization tools such as Docker is a plus
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   💵 Competitive salary paid in USD
  </li>
  <li>
   🏡 Fully remote - work from anywhere
  </li>
  <li>
   🌎 Work with a diverse international team
  </li>
  <li>
   🚀 Exciting projects and a supportive engineering culture
  </li>
  <li>
   📈 Opportunities to grow technically and professionally
  </li>
 </ul>
</div>


Lasting Change Inc

<div>Description:
<p>
 The AI Engineer is Lasting Change's first dedicated AI role, joining an established Data &amp; Innovation team focused on advancing the organization's data and analytics capabilities. This position will design, build, and deploy AI-powered solutions that improve staff effectiveness and enhance services for clients. Initial focus areas include surfacing insights from complex documentation, reducing administrative burden, and supporting faster, more informed decision-making across programs and operations.</p><p>
Working closely with organizational stakeholders and the broader data team, the AI Engineer will leverage curated data assets from Petra, Lasting Change's Microsoft Fabric-based enterprise data lakehouse, to deliver practical, trustworthy, and mission-aligned AI solutions. As the organization's AI capabilities mature, this role will help establish the standards, platforms, and practices that support long-term success.</p><p><b>
Company Conformance Statements / Essential Personal Characteristics</b></p><p>
In the performance of their respective tasks and duties, all employees are expected to conform to the following:</p><ul><li>
Perform quality work within deadlines with or without direct supervision.</li></ul><p>
2. Interact professionally with other employees, customers, and clients.</p><p>
3. Work effectively as a team member.</p><p>
4. Work independently while understanding the necessity for communicating and coordinating work efforts with other employees and organizations.</p><p>
5. Exhibit exceptional integrity in all matters.</p><p>
6. Lead by example.</p>
Requirements:
<p><b>
LLM Application Development</b></p><ul><li>
Design and build LLM-powered applications that help staff work more effectively &mdash; including document processing, content generation, and conversational interfaces.</li><li>
Engineer prompt pipelines with structured outputs, retrieval-augmented generation (RAG), and tool-use patterns tailored to organizational data and workflows.</li><li>
Evaluate, select, and integrate best-in-class LLM and AI platform tooling, with preference for Microsoft Fabric, Azure AI Foundry, and complementary services.</li><li>
Ensure AI applications are reliable, auditable, and designed with responsible AI principles, including transparency, fairness, and appropriate human oversight.</li></ul><p><b>
Agentic Workflows &amp; Process Automation</b></p><ul><li>
Design and deploy agentic workflows that automate multi-step processes, reducing manual effort and improving consistency across operations.</li><li>
Build and integrate MCP (Model Context Protocol) servers to connect AI agents with organizational data sources, internal tools, and external services.</li><li>
Collaborate with operational stakeholders to identify, scope, and deliver automation opportunities with clear business value.</li><li>
Contribute to a disciplined, iterative approach to AI development &mdash; shipping focused solutions, learning from them, and expanding scope over time.</li></ul><p><b>
Data Collaboration &amp; Platform Integration</b></p><ul><li>
Partner closely with the internal data team to leverage curated, trusted datasets from Petra as inputs to AI systems and pipelines.</li><li>
Collaborate on data modeling and governance decisions that support AI use cases without compromising platform integrity.</li><li>
Ensure all AI pipelines are integrated with the organization's data platform, security standards, and access controls.</li><li>
Use Python and SQL fluently across prototyping, feature engineering, and production pipeline development.</li></ul><p><b>
Stakeholder Collaboration &amp; Communication</b></p><ul><li>
Engage directly with program leaders, operations staff, and leadership to understand business problems and define AI solutions with clear, measurable outcomes.</li><li>
Communicate AI system behavior, limitations, and results in plain language to non-technical audiences.</li><li>
Champion responsible, explainable AI use across the organization &mdash; ensuring solutions are trustworthy and aligned with Lasting Change's mission and values.</li><li>
Maintain thorough documentation of all AI systems, prompt designs, agentic workflows, and integration patterns to support maintainability and knowledge transfer.</li></ul><p><b>
Platform Ownership &amp; Continuous Improvement</b></p><ul><li>
Contribute to AI engineering standards and tooling choices that can scale as the organization's capability grows.</li><li>
Leverage AI-assisted development practices to maximize engineering velocity across prototyping, documentation, and testing.</li><li>
Stay current with developments in AI research and tooling; evaluate and introduce new capabilities where they create genuine organizational value.</li><li>
Participate in shaping the long-term AI roadmap, including identifying when and how machine learning capabilities should be introduced over time.</li></ul><p><b>
Essential Functions</b></p><p>
Reasonable accommodations may be made to enable individuals with disabilities to perform these functions.</p><ul><li>
Use of Fingers</li><li>
Feeling</li><li>
Speaking</li><li>
Hearing</li><li>
Repetitive Motions</li><li>
Capable of making sound decisions by use of reasonable and logical judgments.</li><li>
Demonstrated competence in understanding, interpreting, and communicating procedures, policies, information, ideas, and instructions.</li></ul><p><b>
Travel</b></p><p>
Travel may be required occasionally to subsidiary sites and training opportunities.</p><p><b>
Required Experience</b></p><ul><li>
5&ndash;8 years of professional experience in AI, data engineering, software engineering, or a closely related field.</li><li>
Demonstrated expertise in LLM integration, prompt engineering, and building AI-powered applications using modern foundation models.</li><li>
Hands-on experience designing and deploying agentic AI workflows, including tool use and multi-step reasoning; familiarity with agent orchestration frameworks a plus.</li><li>
Experience building or integrating MCP (Model Context Protocol) servers or equivalent agent-to-tool integration patterns.</li><li>
Strong proficiency in Python and SQL; comfortable across prototyping, pipeline development, and production deployment.</li><li>
Experience with cloud AI platforms; Microsoft Fabric, Azure AI Foundry, or equivalent best-in-class tooling strongly preferred.</li><li>
Experience consuming organizational data platforms (lakehouses, warehouses, or similar) as inputs to AI systems.</li><li>
Strong communication skills with the ability to explain AI concepts, system behavior, and trade-offs clearly to non-technical stakeholders.</li><li>
Demonstrated commitment to responsible AI practices including explainability, fairness, and appropriate human oversight.</li><li>
Highly organized, self-directed, and motivated by mission-driven work.</li></ul><p><b>
Preferred Qualifications</b></p><ul><li>
Experience with retrieval-augmented generation (RAG) architectures and vector search platforms (e.g. Azure AI Search, Pinecone, Weaviate).</li><li>
Familiarity with MLOps concepts and an interest in growing into machine learning model development and deployment over time.</li><li>
Exposure to healthcare, human services, or nonprofit data environments.</li><li>
Microsoft Azure AI, Fabric, or equivalent cloud certifications.</li><li>
Experience surfacing AI outputs through Power BI or other BI and reporting platforms.</li><li>
Comfortable working in a greenfield environment where processes and patterns are still being established.</li><li>
Commitment to continuous learning and professional growth in a rapidly evolving field.</li></ul><p><b>
Other Duties</b></p><p>
This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required by the employee. Management reserves the right to assign or reassign duties, activities, and responsibilities to this position at any time, with or without notice.</p></div>

Recutify Inc.

<div><p><b>Role : AI Engineer</b></p>
<p><b>Locatin : Charlotte NC
</b></p><p>We are seeking a highly skilled AI Engineer with a Master's degree in Computer Science, Artificial Intelligence, or a related field to design, develop, and deploy advanced AI/ML systems. This role is centered on building next-generation agentic AI solutions powered by retrieval-augmented generation (RAG), leveraging modern orchestration frameworks such as LangGraph and Model Context Protocol (MCP).<br>
The ideal candidate will have deep expertise in Python-based AI development and hands-on experience designing agent systems capable of reasoning, planning, tool usage, and executing complex multi-step workflows. A strong foundation in end-to-end RAG architectures, including Graph RAG, is required.<br>
</p><p><b>Primary Skill: Artificial Intelligence/Machine Learning</b><br>
<b>Secondary Skill: Python</b><br>
<b>Tertiary Skill: Natural Language Processing</b><br>
</p><p><b>Required Qualifications</b></p>
<ul><li>Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.</li>
<li>Strong proficiency in Python programming, with experience building scalable AI/ML systems.</li>
<li>Hands-on experience with agentic AI frameworks, particularly LangGraph, and emerging standards such as Model Context Protocol (MCP).</li>
<li>Strong experience designing and implementing advanced RAG architectures, including Graph RAG.</li>
<li>Experience with LLM orchestration frameworks such as LangChain, LangGraph, and LlamaIndex.</li>
<li>Proven experience deploying LLM-powered production systems.</li>
<li>Design and implement advanced RAG pipelines using vector databases, embeddings, knowledge graphs, and hybrid retrieval strategies.</li>
<li>Develop agentic AI systems using LangGraph, enabling dynamic task planning, reasoning, tool orchestration, and multi-agent workflows.</li>
<li>Integrate Model Context Protocol (MCP) for standardized context sharing, tool interoperability, and scalable agent communication.</li>
<li>Design memory systems and contextual state management for agent continuity and long-running workflows.</li>
<li>Implement evaluation pipelines, prompt engineering strategies, and guardrails to ensure performance, safety, and reliability.</li>
<li>Apply Model Risk Management (MRM) practices across the AI lifecycle, including model validation, explainability, bias detection, monitoring, and documentation.</li>
<li>Strong experience with Python ML/AI frameworks such as PyTorch, TensorFlow, and Scikit-learn.</li>
<li>Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, Azure AI Search) and semantic retrieval systems.</li>
<li>Deep understanding of agent orchestration patterns, including planning, reflection, tool usage, and multi-agent collaboration.</li>
<li>Experience implementing Graph RAG using knowledge graphs and structured data integration.</li>
<li>Expertise in memory architectures (short-term, long-term, episodic memory) in agent systems.</li>
<li>Strong understanding of LLMOps/MLOps, including CI/CD, observability, monitoring, and performance optimization.</li>
<li>Working knowledge of Model Risk Management (MRM) frameworks including governance, validation, and lifecycle controls.</li>
<li>Familiarity with AI safety and alignment techniques, including guardrails, human-in-the-loop systems, and bias mitigation.</li>
<li>Experience with model evaluation, benchmarking, and explainability tools .</li>
<li>Proficiency with development tools such as GitHub, VS Code, JIRA, and modern engineering workflows.</li>
</ul><p></p><p><b>Desired Qualifications</b></p>
<ul><li>Experience working in an Agile development methodology; experience with RAG and LLM</li>
</ul><p></p><p><b>Intake Notes:</b></p>
<ul><li>Overview of the work being done</li>
<li>Design and develop production-grade Python APIs/services</li>
<li>Deploy and operate applications on OpenShift</li>
<li>Partner with AI/ML engineers to productionize model capabilities into usable backend services</li>
<li>Remediate vulnerabilities in:</li>
<li>Python libraries/dependencies</li>
<li>Container images</li>
<li>OpenShift deployment configurations</li>
<li>Primarily internal collaboration with cross-functional teams such as AI/ML engineers, UI developers, DevOps, and security/compliance stakeholders.</li>
<li>Building Python-based microservices/APIs that expose AI/ML model functionality to downstream applications</li>
<li>Deploying containerized applications to OpenShift and configuring manifests, services, routes, and secrets</li>
<li>Integrating backend APIs with Angular-based front-end applications</li>
<li>Performing remediation of security findings in Python dependencies and container images</li>
<li>Automating deployment workflows using CI/CD pipelines aligned with OpenShift standards</li></ul></div><p></p>

Digital Phantom

<p>Digital Phantom is a fast-growing digital marketing and technology company delivering innovative solutions across AI, automation, software development, and digital transformation. We are looking for a highly skilled AI Engineer to join our growing team and help build intelligent systems that drive real business impact.</p><p>Responsibilities</p><ul><li>Design, develop, and deploy AI/ML models for real-world business applications</li><li>Build and optimize LLM-based solutions, AI agents, and automation systems</li><li>Work with structured and unstructured datasets for model training and evaluation</li><li>Integrate AI solutions into web applications, CRMs, and business workflows</li><li>Collaborate with developers, marketers, and product teams to create scalable AI products</li><li>Monitor model performance and continuously improve system accuracy</li><li>Stay updated with the latest advancements in Artificial Intelligence and Machine Learning</li></ul><p>Requirements</p><ul><li>3&ndash;5 years of professional experience in AI Engineering, Machine Learning, or related fields</li><li>Strong proficiency in Python and AI frameworks such as TensorFlow, PyTorch, or Scikit-learn</li><li>Experience working with LLMs, OpenAI APIs, LangChain, vector databases, or RAG systems</li><li>Familiarity with cloud platforms such as AWS, Azure, or Google Cloud</li><li>Understanding of NLP, deep learning, and data engineering concepts</li><li>Experience with automation tools and AI integrations is a plus</li><li>Strong problem-solving and communication skills</li><li>Bachelor&rsquo;s degree in Computer Science, AI, Software Engineering, or a related field</li></ul><p>Preferred Skills</p><ul><li>Experience building AI chatbots and conversational systems</li><li>Knowledge of prompt engineering and fine-tuning AI models</li><li>Familiarity with Docker, APIs, Git, and CI/CD workflows</li><li>Understanding of digital marketing automation and analytics is a bonus</li></ul><p>What We Offer</p><ul><li>Competitive salary package</li><li>Opportunity to work on cutting-edge AI projects</li><li>Flexible and collaborative work environment</li><li>Career growth and leadership opportunities</li><li>Exposure to international clients and projects</li></ul><p>Pay: Up to Rs300,000.00 per hour</p><p>Work Location: Remote</p>

BridgeNexus Technologies Inc

<p>only <b>GC </b>and <b>USC VISA:</b></p><p>We are seeking a highly skilled AI Engineer with hands-on experience in agent development, Retrieval-Augmented Generation (RAG), agentic workflows, and platforms such as Cursor AI. The ideal candidate will have a strong developer mindset and expertise in integrating APIs and building intelligent systems that can reason, act, and interact across tools and data sources.</p><p><b>Key Responsibilities:</b></p><p>&middot; Design, develop, and optimize AI agents capable of reasoning, decision-making, and tool usage</p><p>&middot; Implement and fine-tune RAG pipelines for contextual knowledge integration</p><p>&middot; Develop, integrate, and manage agentic workflows across APIs, vector stores, and third-party tools</p><p>&middot; Leverage Cursor AI and similar platforms to prototype and deploy agent-based applications</p><p>&middot; Collaborate with product teams to implement AI-driven features with seamless developer experience</p><p>&middot; Build scalable APIs for model access, integration, and service orchestration</p><p>&middot; Stay updated with the latest in LLMs, agent orchestration frameworks, and AI tooling</p><p>Required Skills &amp; Qualifications:</p><p>&middot; Strong programming skills in Python or equivalent (Go/Node.js is a plus)</p><p>&middot; Experience in developing autonomous agents and agentic workflows using frameworks like LangChain, AutoGen, or similar</p><p>&middot; Hands-on with Cursor AI for development, debugging, and agent orchestration</p><p>&middot; Experience building and consuming RESTful APIs</p><p>&middot; Proficiency in RAG architectures, including vector stores (e.g., FAISS, Pinecone, Weaviate), embedding models, and retrieval tuning</p><p>&middot; Experience with prompt engineering, tool calling, and multi-agent collaboration setups</p><p>&middot; Solid understanding of LLMs, their fine-tuning strategies, and evaluation frameworks</p><p>Pay: $55.00 - $60.00 per hour</p><p>Benefits:</p><ul><li>Health insurance</li></ul><p>Work Location: In person</p>

LexisNexis Legal & Professional

<p></p><div><p><b>Applied AI Engineer<br>
</b></p><p></p><p><b>About the role
</b></p><p>LexisNexis Legal &amp; Professional is hiring an Applied AI Engineer to help shape the next generation of AI-powered legal products and developer experiences.
</p><p>As an Applied AI Engineer at LexisNexis, you will partner with internal teams and enterprise stakeholders to help build AI-powered applications and workflows on top of LexisNexis AI platforms, legal content, and AI-powered workflows and agent-based capabilities. You will work directly with engineering, AI engineering, and data science teams to design and implement production AI applications, agent workflows, and scalable LLM-powered experiences that support complex legal and professional workflows.
</p><p>This role sits at the intersection of AI engineering, data scientist, developer enablement, and customer engagement. You will partner with Product, Engineering, Applied Science, and AI Platform teams to support implementation decisions, accelerate AI adoption, and help teams adopt reusable AI engineering patterns and implementation best practices.
</p><p>This is a deeply hands-on role focused on building, prototyping, and iterating on AI-powered experiences. The ideal candidate combines strong software engineering fundamentals with practical experience deploying LLM applications, agent systems, and AI-native workflows in production environments.<br>
</p><p></p><p><b>What you&rsquo;ll do
</b></p><p><b>Start with customers
</b></p><ul><li>Spend real time with lawyers, legal operations teams, and our internal subject-matter experts &mdash; in their offices, on their calls, watching their workflows. Develop a strong understanding of customer workflows and operational challenges through direct engagement.
</li></ul><ul><li>Translate ambiguous, half-formed customer pain into crisp problem statements the team can build against.
</li></ul><ul><li>Collaborate closely with customers and internal stakeholders to prototype, validate, and refine AI-powered workflows and user experiences based on customer feedback and observed user needs.
</li></ul><ul><li>Bring the customer voice back into our roadmaps, our model choices, and our trade-offs.
</li></ul>Occasional travel to customer sites may be required to better understand workflows and gather product feedback.<br>
<ul><li>
</li></ul><p></p><p><b>Build AI-powered applications and workflows
</b></p><ul><li>Contribute to AI-powered applications and workflows for legal and professional use cases, including leveraging existing RAG pipelines, research assistants, and related AI capabilities developed by ML engineering teams.
</li></ul><ul><li>Implement and iterate on LLM application capabilities such as prompt engineering, multi-step workflows, tool calling, and lightweight agent patterns in collaboration with machine learning engineering teams.
</li></ul><ul><li>Contribute to scalable orchestration layers for prompting, retrieval, and tool integration across AI services.
</li></ul><ul><li>Work with frameworks such as LangChain, LangGraph, LlamaIndex, MCP/A2A, OpenAI SDKs, Google ADK, and/or Anthropic/Claude APIs to prototype and productionize AI capabilities.
</li></ul>Participate in experimentation, testing, and performance optimization activities for LLM-based applications in production environments.<br>
<ul><li>
</li></ul><p></p><p><b>Contribute to AI Engineering Enablement
</b></p><ul><li>Support adoption of AI engineering practices by helping software engineering teams incrementally integrate machine learning and generative AI capabilities into existing products and workflows, in collaboration with AI/ML engineering teams.
</li></ul><ul><li>Promote reusable AI/ML engineering standards, tooling, and best practices that reduce friction for teams adopting AI and machine learning technologies, while aligning with recommendations from data science and AI platform teams.
</li></ul><ul><li>Help software engineers expand their capabilities in ML-oriented development for applicable use cases without requiring deep data science specialization.
</li></ul><ul><li>Support teams in adopting AI-assisted development workflows through prototyping, architecture collaboration, and hands-on engineering support.
</li></ul><ul><li>Contribute to engineering for LLM applications, AI workflows, and AI-enabled product development.
</li></ul><ul><li>Assist in building evaluation, monitoring, and observability tooling to improve AI application quality, reliability, and developer visibility.
</li></ul><ul><li>Collaborate with Product, Engineering, Data Science, UX, Security, and Legal teams to support the adoption of AI and machine learning capabilities across products and platforms.
</li></ul><ul><li>Create technical documentation, sample applications, tutorials, and implementation guides to help engineers transition from traditional software development to AI-powered application development.
</li></ul>Partner with engineering teams to introduce modern AI engineering practices, reusable tooling, and machine learning workflows into existing software development processes.<br>
<ul><li>
</li></ul><p></p><p><b>Bring others with you
</b></p><ul><li>Partner closely with data scientists, machine learning engineers, designers, product managers, legal SMEs, and platform engineering teams. Effective AI product development depends on strong cross-functional collaboration and respect for each discipline&rsquo;s expertise.
</li></ul><ul><li>Collaborate with and support engineering teams in adopting modern AI engineering practices, agent workflows, and evaluation approaches.
</li></ul><ul><li>Communicate clearly with people who aren&rsquo;t engineers &mdash; especially lawyers &mdash; and adapt your language to the audience without dumbing things down.
</li></ul><ul><li>Contribute feedback and implementation learnings to shared AI platform capabilities, tooling, and developer workflows.
</li></ul>Contribute constructively to technical discussions, collaborate effectively across teams, and remain open to feedback and evolving implementation approaches.<br>
<ul><li>
</li></ul><p></p><p><b>Required qualifications
</b></p><ul><li>6+ years of experience as a Software Engineer, AI Engineer, Platform Engineer, or related technical role.
</li></ul><ul><li>Strong production experience building LLM-powered applications and deployment at scale.
</li></ul><ul><li>Strong programming skills in Python and experience building scalable production services and APIs.
</li></ul><ul><li>Experience designing and implementing AI application architectures in cloud-native environments.
</li></ul><ul><li>Hands-on experience with modern AI engineering frameworks and tooling such as LangChain, LangGraph, LlamaIndex, OpenAI APIs, Anthropic APIs, MCP, or equivalent systems.
</li></ul><ul><li>Experience building AI workflows involving retrieval, tool calling, orchestration, context management, and structured generation.
</li></ul><ul><li>Familiarity with AI observability, evaluation frameworks, and production monitoring.
</li></ul><ul><li>Experience deploying and operating AI systems on AWS, Azure, or GCP.
</li></ul><ul><li>Comfortable working in evolving environments and collaborating across teams to deliver AI-powered features and workflows.
</li></ul><ul><li>Strong communication and collaboration skills with the ability to work effectively across engineering, product, and business teams.
</li></ul>Experience contributing to production systems and collaborating on practical implementation trade-offs.<br>
<ul><li>
</li></ul><p></p><p><b>Preferred qualifications
</b></p><ul><li>Experience in legal technology, enterprise SaaS, compliance, financial services, healthcare, or other regulated industries.
</li></ul><ul><li>Experience building AI copilots, AI assistants, workflow automation systems, or multi-agent platforms.
</li></ul><ul><li>Familiarity with developer platforms, SDK development, API productization, or AI platform engineering.
</li></ul><ul><li>Experience facilitating technical workshops, hackathons, or developer enablement initiatives.
</li></ul><ul><li>Strong understanding of AI UX and conversational workflow system design.
</li></ul><ul><li>Experience with AI evaluation, guardrails, policy enforcement, and responsible AI deployment.
</li></ul><ul><li>Familiarity with inference optimization, LLM serving infrastructure, or AI infrastructure tooling.
</li></ul><ul><li>Full-stack or frontend engineering experience for rapid prototyping and developer experience optimization.
</li></ul>Open-source contributions, technical blogging, conference speaking, or AI engineering community involvement.<br>
<ul><li>
</li></ul><p></p><p><b>About LexisNexis Legal &amp; Professional
</b></p><p>LexisNexis Legal &amp; Professional is a global leader in legal information and analytics, serving customers in more than 150 countries. We are investing aggressively in generative AI, agentic systems, and AI-native workflows that help legal professionals research faster, draft with confidence, and make better decisions in complex legal environments.
</p><p>Our mission is to build trustworthy enterprise-grade AI systems that combine cutting-edge innovation with the accuracy, transparency, and reliability required in the legal industry.
</p><p>LexisNexis is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
</p>&amp;#xa;&amp;#xa;U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local market rates.&amp;#xa;&amp;#xa;&amp;#xa;&amp;#xa;This job is eligible for an annual incentive bonus.&amp;#xa;&amp;#xa;
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