intelligence engineer

FlairsTech

<div><div><div><div><div><p>Requirements and responsibilities</p><br>
<div><h2 class="jobSectionHeader"><b>About the Engagement</b></h2>
<p>FlareTech is building &quot;Context Intelligence,&quot; an AI platform centered on a proprietary &quot;process neural net&quot; architecture. Rather than relying on standard NLP or data warehouses, the platform builds model graphs that reverse-engineer data models directly from the business, enabling clients to inject knowledge management indexed to their own goals and strategy. FlareTech has secured a Proof of Concept with a major global enterprise client (hundreds of thousands of employees) and needs to accelerate delivery toward an October 1 POC milestone, with full production deployment targeted for November/December.</p>
<p>This role owns the &quot;Context&quot; domain specifically &mdash; context artifacts, ingestion workers, and fine-tuning &mdash; while the existing FlareTech team continues building out process automation and the rest of the platform in parallel.</p>
<h2 class="jobSectionHeader"><b>Main Responsibilities</b></h2>
<ul><li>Own the Context domain end-to-end: context artifacts, ingestion workers, and the fine-tuning pipeline within the Context Intelligence platform.</li>
<li>Design, implement, and operate production-grade fine-tuning workflows for localized (on-prem / self-hosted) LLMs.</li>
<li>Build and maintain ingestion workers that structure and feed data into the model graph architecture.</li>
<li>Support the reverse-engineering of client data models into model graphs, in line with FlareTech&rsquo;s process-neural-net approach.</li>
<li>Deploy and manage local LLM hosting to meet enterprise confidentiality requirements, as an alternative to cloud-hosted LLM APIs.</li>
<li>Engage directly with Darshan (VP of IT) to scope work, set priorities, and integrate deliverables into the critical path for the October 1 POC.</li>
<li>Coordinate with the existing platform team to ensure the Context domain integrates cleanly with process automation and other platform areas.</li>
<li>Prepare technical documentation on the process neural net / model graphing architecture to support client technical due diligence.</li>
<li>Help accelerate the POC timeline, then transition the Context domain into full production for the November/December deployment.</li>
</ul><h2 class="jobSectionHeader"><b>Required Skills &amp; Experience</b></h2>
<ul><li>Production experience fine-tuning LLMs &mdash; has shipped fine-tuned models into a live product, not only prompt engineering or inference-time RAG.</li>
<li>Hands-on experience deploying and operating localized / on-prem / self-hosted LLMs (e.g., via vLLM, TGI, Ollama, or comparable serving stacks).</li>
<li>Strong understanding of Retrieval-Augmented Generation (RAG) architectures, and how fine-tuning and RAG complement each other.</li>
<li>Experience building data ingestion pipelines &mdash; workers that clean, structure, and prepare data for model consumption.</li>
<li>Familiarity with graph-based or structured knowledge representations (model graphs, knowledge graphs), including reverse-engineering data models from unstructured or semi-structured sources.</li>
<li>Comfortable operating in a fast-moving, ambiguous R&amp;D environment against a hard external deadline (client POC).</li>
<li>Strong communication skills &mdash; will scope work directly with a client-side VP of IT with minimal intermediary process.</li>
<li>A security- and confidentiality-first mindset, understanding why enterprise clients require local LLM deployment over cloud APIs.</li>
</ul><h2 class="jobSectionHeader"><b>Nice to Have</b></h2>
<ul><li>Experience building no-code or low-code AI/workflow automation platforms.</li>
<li>Exposure to agentic frameworks or multi-agent systems (useful context, even though this platform favors fine-tuning over complex agent authoring).</li>
<li>Background in enterprise knowledge management or business process automation.</li>
<li>Experience with platform/marketplace business models involving third-party extensibility.</li></ul></div></div></div></div></div></div><div></div>

AI Engineer

LTC Solutions, LLC

<div><p>LTC Solutions, LLC is a small business with a huge commitment to supporting our employees and providing quality services to our government clients. Our employees have an entrepreneurial spirit, a passion for excellence, and a proactive approach to providing the best possible solutions to our clients. If you are committed to building excellent client relationships, providing consistent superior-quality work, and taking initiative to understand your clients&rsquo; needs, we would like to meet you!</p>
<p>
LTC offers a dynamic team setting and generous benefits (including 401K, PTO, and Health, Dental, Vision, Life and Disability Insurance).</p>
<p>
POSITION DESCRIPTION: AI Engineering Support</p><br>
<p><b>
Location:</b> Pentagon, Arlington, VA (Hybrid)</p>
<p><b>
Status:</b> Contingent Hire &ndash; Full-Time &ndash; Hybrid</p>
<p><b>
Clearance:</b> Active Top Secret/SCI Clearance Required</p>
<p><b>
MUST HAVE:</b> Demonstrated experience <b>supporting Department of Defense data engineering</b>, business intelligence, data governance, automated data pipelines, and enterprise analytics supporting operational decision-making.</p>
<p>
Position Summary</p>
<p>
The AI Engineer / Research Analyst provides mid-level data engineering, business intelligence, and applied analytics support to Headquarters Marine Corps (HQMC), Installations and Logistics (I&amp;L), and the Global Positioning Network (GPN) Program. Working in a hybrid capacity supporting the Pentagon, the position develops and maintains data extraction, transformation, validation, and integration processes that convert raw operational data into secure, authoritative datasets supporting advanced analytics and executive decision-making.</p>
<p>
The AI Engineer supports enterprise data engineering activities by developing automated queries, reusable data pipelines, data quality processes, and business intelligence solutions while ensuring compliance with Department of War (DoW), U.S. Marine Corps (USMC), and Department of Defense cybersecurity, records management, and data governance requirements. Working under the direction of senior analytics leadership, the position supports the development of scalable data architectures that enable predictive analytics, dashboard development, artificial intelligence, and operational reporting.</p>
<p>
The position collaborates with Headquarters Marine Corps organizations, Government data owners, system administrators, and analytics personnel to improve data accessibility, quality, security, and enterprise reporting capabilities.</p>
<p>
Required Qualifications</p>
<ul>
<li>U.S. Citizen with an <b>Active Secret security clearance</b> and ability to obtain a CAC card.</li>
<li>Bachelor's degree in <b>Computer Science, Data Science, Information Systems, Software Engineering, Data Engineering, Business Analytics, Mathematics</b>, or a related discipline.</li>
<li><b>Four (4) to seven (7) years</b> of experience supporting Department of Defense data engineering, business intelligence, database development, analytics, or enterprise information management.</li>
<li>Experience designing and developing automated data extraction, transformation, and loading (ETL/ELT) processes.</li>
<li>Experience writing complex SQL queries and developing reusable database scripts.</li>
<li>Experience using <b>Python</b>, SQL, and data transformation libraries for automation and data preparation.</li>
<li>Experience developing secure data pipelines and preparing authoritative datasets for reporting and analytics.</li>
<li>Experience supporting enterprise data governance, metadata management, and data quality initiatives.</li>
<li>Working knowledge of Department of Defense cybersecurity requirements, secure data handling procedures, and records management practices.</li>
<li>Experience supporting business intelligence environments using Power BI, Tableau, Microsoft Fabric, or similar reporting platforms.</li>
<li>Strong analytical, technical writing, communication, and organizational skills.</li>
</ul>
<p>Preferred Qualifications</p>
<ul>
<li>Master's degree in <b>Data Science, Information Systems, Computer Science, Software Engineering, Business Analytics</b>, or a related discipline.</li>
<li>Experience supporting Headquarters Marine Corps, Department of the Navy, Joint Staff, or other Department of Defense headquarters organizations.</li>
<li>Experience designing enterprise data warehouses, reporting architectures, or business intelligence platforms.</li>
<li>Experience with Azure Data Factory, Microsoft Fabric, Databricks, Snowflake, or equivalent enterprise data engineering platforms.</li>
<li>Experience supporting DevSecOps, CI/CD pipelines, Git, or Azure DevOps.</li>
<li>Familiarity with artificial intelligence and machine learning data preparation techniques.</li>
<li>Experience implementing enterprise data governance frameworks and data catalog solutions.</li>
<li>Knowledge of DoD Zero Trust Architecture, RMF, and cybersecurity compliance requirements.</li>
</ul>
<p>Primary Duties</p>
<ul>
<li>Develop and maintain automated data extraction, transformation, validation, and loading (ETL/ELT) processes supporting GPN analytics and enterprise reporting.</li>
<li>Create and optimize complex SQL queries, stored procedures, and reusable scripts that automate recurring data collection and reporting activities.</li>
<li>Develop secure, reusable data pipelines that prepare authoritative datasets for analytics, artificial intelligence, business intelligence, and executive reporting.</li>
<li>Validate, cleanse, normalize, and integrate structured and unstructured data from multiple Government information systems.</li>
<li>Implement enterprise data quality controls, validation routines, reconciliation processes, and metadata documentation to improve data integrity.</li>
<li>Support development and maintenance of enterprise business intelligence architectures, reporting databases, and visualization back-end environments.</li>
<li>Prepare datasets supporting predictive analytics, machine learning models, simulation activities, and operational research efforts performed by senior AI engineers and data scientists.</li>
<li>Collaborate with Government stakeholders to define data standards, business rules, data dictionaries, and governance policies.</li>
<li>Ensure compliance with Department of War (DoW), U.S. Marine Corps (USMC), Department of Defense cybersecurity policies, records management requirements, and enterprise data governance standards.</li>
<li>Document database structures, transformation logic, automated workflows, technical procedures, and data lineage supporting long-term sustainment.</li>
<li>Assist with troubleshooting data quality issues, system integration challenges, and reporting inconsistencies.</li>
<li>Support implementation of secure data architectures that improve availability, reliability, scalability, and performance of analytical systems.</li>
<li>Coordinate with AI Engineers, Data Analysts, Business Intelligence developers, Government personnel, and system administrators to support enterprise analytics initiatives.</li>
<li>Participate in configuration management, version control, testing, deployment, and continuous improvement of enterprise data engineering solutions.</li>
<li>Perform additional data engineering, business intelligence, analytics, automation, and governance duties necessary to accomplish contract requirements.</li>
</ul>
<p>Preferred Technical Skills</p>
<ul>
<li>Python</li>
<li>SQL</li>
<li>Power BI</li>
<li>Tableau</li>
<li>Microsoft Fabric</li>
<li>Azure Data Factory</li>
<li>Azure Synapse Analytics</li>
<li>Databricks</li>
<li>Snowflake</li>
<li>PostgreSQL</li>
<li>Microsoft SQL Server</li>
<li>Git</li>
<li>Azure DevOps</li>
<li>ETL/ELT Development</li>
<li>Data Warehousing</li>
<li>REST APIs</li>
<li>JSON/XML</li>
<li>Data Governance</li>
<li>Metadata Management</li>
<li>Data Lineage</li>
<li>RMF</li>
<li>Zero Trust Architecture</li>
</ul>
<p><b>LTC Solutions is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.</b></p></div>

AI Engineering Support US Citizens only, active TS/SCI clearance required

Kirkland & Ellis

<div><p><b>About Kirkland &amp; Ellis</b>
</p><p>At Kirkland &amp; Ellis, we don&rsquo;t just meet the standard for legal excellence &mdash; we set it. Our culture is built on teamwork, ingenuity and an unwavering commitment to continuous growth. We tackle the most sophisticated legal challenges with bold ideas and innovative solutions, powered by the exceptional experience and ambition of our 7,000+ people, including 4,000+ attorneys, across 24 offices worldwide. Our dedicated professionals share our lawyers&rsquo; commitment to excellence and show up each day to do meaningful work that helps drive global business, investment and innovation forward.</p><p><b>
What You&rsquo;ll Do</b>
</p><p>Are you passionate about turning complex data into meaningful insights that drive business decisions?</p><p>
As a Business Intelligence Data Modeler Engineer II, you&rsquo;ll play a critical role in shaping how data is structured, accessed, and for enterprise business intelligence. Partnering closely with business analysts, data engineers, and business stakeholders, you&rsquo;ll design and support development of data models that power reporting, analytics. This role blends technical expertise with business insight, giving you the opportunity to influence how data supports enterprise-wide decision-making.</p><div><ul><li><br>
Data Modeling Design: Create and maintain conceptual, logical, and physical data models that support reporting and analytics across enterprise systems.</li><li>Business Partnership: Collaborate with stakeholders to translate business needs into scalable data structures and solutions.</li><li>ETL Development Support: Contribute to the design of Extract, Transform, Load (ETL) processes to ensure efficient data movement into Business Intelligence (BI) platforms and warehouses.</li><li>Data Quality &amp; Validation: Implement checks and rules to ensure data accuracy, consistency, and reliability across systems.</li><li>Performance Optimization: Continuously monitor and refine data models and database performance for efficient querying and reporting.</li><li>Documentation &amp; Governance: Maintain clear documentation of models, schemas, and data flows while adhering to data governance standards.</li><li>Data Security: Help design access controls and security measures to protect sensitive data.</li><li>Advanced Querying: Develop and utilize Structured Query Language (SQL) queries for ad hoc analysis, troubleshooting, and data validation.</li><li>Agile Collaboration: Participate in Agile workflows across analysis, development, quality assurance (QA), and user acceptance testing (UAT) phases as a data subject matter expert.</li><li>Domain Expertise: Build strong knowledge of business systems and data domains to support strategic initiatives.</li><li>Continuous Learning: Stay current with evolving technologies and industry trends in data modeling and analytics.</li></ul></div><p><b><br>
What You&rsquo;ll Bring</b>
</p><ul><li>Education: Bachelor&rsquo;s degree in computer science, a related field, or equivalent practical experience.</li><li>Experience: 7+ years of experience in data modeling, data warehousing, and ETL processes.</li></ul><div>
Required<br>
<ul><li>Data Modeling Expertise: Strong Hands-on experience of dimensional modeling, fact tables, star/snowflake schemas, slowly changing dimensions (SCDs), and tools like Erwin.</li><li>Technical Skills: Expertise with SQL (including Transact-SQL) and deep experience with relational database systems such as Microsoft SQL Server.</li><li>Data Engineering Knowledge: Experience with data pipelines using ETL or Extract, Load, Transform (ELT) techniques and tools such as Azure Data Factory (ADF) to load data into analytics data marts, data warehouses and data lakes. Experience with analytics data platforms such as Azure Synapse Analytics, OneLake or Microsoft Fabric.</li><li>Analytics &amp; BI Tools: Familiarity with Business Intelligence (BI) platforms such as Microsoft Power BI and Qlik Sense, and experience supporting enterprise reporting.</li><li>Programming &amp; Scripting: Exposure to Python, PySpark, Databricks, or programming languages like Java or C# is a plus.</li><li>Data Governance &amp; Security: Understanding of data governance principles, access controls, and data protection best practices.</li><li>Business Acumen: Experience working with operational analytics domains such as Human Resources (HR), Finance, or Risk Management; professional services industry experience is a plus.</li><li>Collaboration &amp; Communication: Strong problem-solving, interpersonal, and communication skills with the ability to work cross-functionally.</li><li>Work Style: Highly organized, self-motivated, and able to thrive in a fast-paced, Agile project environment managing multiple priorities.</li></ul></div><p>
If you&rsquo;re ready to help shape how data drives smarter decisions and deliver impactful insights as a Business Intelligence Data Modeler Engineer II, we&rsquo;d love to hear from you!<br>
</p><p><b>Compensation</b>
</p><p>The base salary range below represents the low and high end of the salary range for this position in Chicago. This range may differ based on your geographic location and cost of living considerations. At Kirkland &amp; Ellis, we consider compensation more than just a base salary. We offer an exceptional range of flexible benefits including comprehensive healthcare, paid time off, and retirement. We also offer personal support and tailored learning and development opportunities all designed to help you realize your full potential both in life and at work.</p><p>
Compensation Range:</p><p>
Chicago: $116,000 - $144,000</p><p><b>
How to Apply</b>
</p><p>Thank you for your interest in Kirkland &amp; Ellis LLP. To complete an application and submit your resume, please click &quot;Apply Now.&quot;</p><p><i>
Don't meet every job requirement? That's okay! If you're excited about this role but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others at Kirkland.</i></p><p>
</p><p><b>Equal Employment Opportunity</b>
</p><p>All employment decisions, including the recruiting, hiring, placement, training availability, promotion, compensation, evaluation, disciplinary actions, and termination of employment (if necessary) are made without regard to the employee&rsquo;s race, color, creed, religion, sex, pregnancy or childbirth, personal appearance, family responsibilities, sexual orientation or preference, gender identity, political affiliation, source of income, place of residence, national or ethnic origin, ancestry, age, marital status, military veteran status, unfavorable discharge from military service, physical or mental disability, or on any other basis prohibited by applicable law. #LI-Hybrid #LI-CF1</p></div>

Business Intelligence Data Modeler Engineer II

pointer infotech L.L.C

<p><b>Overview</b></p><p>Join our innovative team as an AI Engineer and be at the forefront of developing cutting-edge artificial intelligence solutions that transform data into actionable insights. In this dynamic role, you will design, implement, and optimize AI models and machine learning frameworks to solve complex problems across various domains. Your expertise will drive the deployment of scalable AI systems, leveraging big data technologies and cloud services to deliver impactful results. This position offers an exciting opportunity to work with advanced tools and methodologies in a collaborative environment dedicated to pushing the boundaries of AI innovation.</p><p><b>Responsibilities</b></p><ul><li><b>Job Summary:</b></li><li>We are looking for an experienced AI Engineer / Senior AI Architect with strong expertise in Agentic AI, Conversational AI, and AI solution development. The ideal candidate will have hands-on experience building AI solutions across Microsoft and Google ecosystems.Key Skills &amp; Responsibilities:Develop Agentic AI solutions, conversational agents, and virtual assistants.Hands-on experience with Microsoft Foundry and Azure AI services.Experience with Azure AI Search, Azure AI Language, Power Platform, and Copilot Studio.Develop AI conversational solutions using Google Dialogflow CX, Google Conversational Agents, and Google CCAI Services.Build and integrate APIs and web services with AI applications.Experience with NLP, Generative AI, LLMs, and AI/ML.Develop and maintain SharePoint Online solutions using Microsoft Power Platform.Train, deploy, monitor, and optimize AI models.Create Looker dashboards for monitoring AI agent performance.Strong programming skills in C#, .NET, JavaScript, or Python.Ensure AI solutions follow security, privacy, governance, and responsible AI practices.Collaborate with business SMEs and cross-functional technical teams.Lead AI Proof of Concept (POC) initiatives and present AI solutions to stakeholders.Required Experience:5+ years of IT experience.2+ years of AI Conversational Agent implementation experience.1+ year of Power Platform experience.Mandatory: Agentic AI development using Microsoft Foundry.Mandatory: SharePoint Online + Microsoft Power Platform.Mandatory: Google Conversational Agents / Dialogflow CX / Google CCAI Services.Bachelor's degree in Computer Science, Information Systems, or related field, or equivalent experience.*</li><li>No Visa sponsorship is available this time</li></ul><p>Pay: $65.00 - $70.00 per hour</p><p>Work Location: In person</p>

MOZN

<div>
 <strong>
  <strong>
   About Mozn
   <br/>
   <br/>
  </strong>
 </strong>
 <p>
  MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.
  <br/>
  <br/>
  We're a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.
  <br/>
  <br/>
  If you're passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.
 </p>
 <strong>
  <strong>
   About the role
   <br/>
   <br/>
  </strong>
 </strong>
 <p>
  We are looking for a AI Engineer to lead the design, deployment, and optimization of machine learning and generative AI solutions. The role focuses on applying advanced ML techniques to solve real-world challenges across government and enterprise clients in Saudi Arabia.
 </p>
 <strong>
  What you'll do
  <br/>
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Designing, building, and scaling machine learning models and infrastructure
  </li>
  <li>
   Deploying deep learning and generative models into production for public and private sector projects
  </li>
  <li>
   Optimizing ML training and inference for performance, latency, and scalability
  </li>
  <li>
   Monitoring, retraining, and improving deployed ML models
  </li>
  <li>
   Driving consultation efforts, providing expert guidance to client stakeholders
  </li>
  <li>
   Own the end-to-end delivery of AI solutions, including data pipelines, model development, backend services, APIs, integrations, user interfaces, deployment, and operations
  </li>
  <li>
   Design and build data ingestion, transformation, and processing pipelines for structured and unstructured data
  </li>
  <li>
   Develop backend services and APIs to expose AI capabilities securely and reliably
  </li>
  <li>
   Build or contribute to frontend applications, dashboards, and interfaces for AI-powered solutions
  </li>
  <li>
   Integrate AI solutions with enterprise systems, databases, authentication services, and third-party platforms
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's or master's degree in computer science or related field
  </li>
  <li>
   3-5 years of experience across software engineering, ML engineering, data science, data engineering and generative AI
  </li>
  <li>
   Strong track record of projects across public and private sectors
  </li>
  <li>
   Expertise in Python, TensorFlow, PyTorch, ONNX, and ML deployment frameworks
  </li>
  <li>
   Expertise in containerization and orchestration technologies (Docker, Kubernetes), with hands-on experience in ML lifecycle management (MLflow) and local LLM deployment frameworks (Ollama)
  </li>
  <li>
   Skilled in on-premise infrastructure design and enterprise architecture frameworks, with strong adherence to security and compliance best practices
  </li>
  <li>
   Deep understanding of hardware provisioning for local LLM deployments (GPU, RAM, and storage optimization) and secure network configurations for internal AI services
  </li>
  <li>
   Experience with cloud ML environments (SageMaker, Vertex AI, OCI Data Science)
  </li>
  <li>
   Familiarity with MLOps practices and automation pipelines
  </li>
  <li>
   Strong end-to-end engineering capabilities across AI, data engineering, backend development, APIs, integrations, and application deployment
  </li>
  <li>
   Experience building data ingestion, transformation, and processing pipelines
  </li>
  <li>
   Familiarity with backend frameworks such as FastAPI, Flask, Django, Node.js, or equivalent technologies
  </li>
  <li>
   Experience designing and consuming REST APIs, webhooks, and enterprise integration interfaces
  </li>
  <li>
   Working knowledge of frontend technologies such as React, Next.js, JavaScript, TypeScript, HTML, and CSS
  </li>
  <li>
   Experience integrating AI solutions with databases, enterprise applications, identity and access management systems, and third-party services
  </li>
  <li>
   Ability to independently build functional AI applications from prototype through production
  </li>
  <li>
   Experience effectively using AI-assisted software development tools to accelerate prototyping and delivery
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space
  </li>
 </ul>
 <ul>
  <li>
   You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best
  </li>
 </ul>
 <ul>
  <li>
   The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best
  </li>
 </ul>
 <ul>
  <li>
   You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI
  </li>
 </ul>
 <ul>
  <li>
   We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves
  </li>
 </ul>
</div>


Dechert LLP

<p></p><div><div><div><div><div><div><div><div><div>Dechert, LLP is a global specialist law firm focused on high end legal work. The AI Engineer partners directly with attorneys, legal professionals, and business-services teams to identify, design, build, and deploy secure AI-enabled solutions that improve the delivery of legal services and firm operations. This role operates at the intersection of business discovery, rapid application development, artificial intelligence, automation, and enterprise technology.
</div><div></div><div>The role translates complex legal and operational needs into practical, scalable solutions&mdash;including generative AI applications, retrieval-augmented generation (RAG) solutions, workflow automations, intelligent agents, integrations, and custom web applications.
</div><div></div><div>The position is part of the IT Applications rapid-development function and is responsible for moving high-value opportunities from idea through proof of concept, pilot, production readiness, and transition to the appropriate enterprise applications, platform, or operations team for long-term support. The engineer works within the firm&rsquo;s security, privacy, data governance, architecture, and AI-risk-management standards.
 </div><div></div><div><b>ESSENTIAL JOB FUNCTIONS:</b>
</div><ul><li>Partner with attorneys, practice groups, legal project management, knowledge management, finance, risk, client development, and business-services teams to understand workflows, pain points, and desired outcomes.</li>
<li>Facilitate technical discovery sessions; assess business problems for AI, automation, workflow, integration, and custom application opportunities.</li>
<li>Rapidly design and develop proof-of-concept and pilot solutions using approved AI platforms, APIs, low-code tools, workflow automation platforms, and custom development technologies.</li>
<li>Build secure AI-enabled applications, including generative AI assistants, document and knowledge-search solutions, RAG applications, workflow copilots, intelligent agents, and decision-support tools.</li>
<li>Develop and maintain integrations among firm applications, document repositories, knowledge systems, data platforms, collaboration tools, and approved third-party services.</li>
<li>Design AI solutions that appropriately address data classification, confidentiality, ethical use, model limitations, human review, auditability, access controls, retention, and regulatory obligations.</li>
<li>Work with enterprise solutions architecture, information security, privacy, records management, risk management, and legal teams to ensure solutions meet global firm standards before production deployment.</li>
<li>Evaluate and select appropriate technical approaches based on business value, solution complexity, data sensitivity, scalability, supportability, and time-to-value.</li>
<li>Develop reusable components, integration patterns, prompt libraries, evaluation methods, documentation, and technical standards that accelerate future AI and automation delivery.</li>
<li>Conduct testing, quality assurance, user acceptance testing, model evaluation, and performance monitoring for AI-enabled solutions.</li>
<li>Establish solution success measures, such as time saved, adoption, accuracy, user satisfaction, process-cycle reduction, risk reduction, and business impact.</li>
<li>Create technical documentation, architecture diagrams, support materials, operating procedures, and knowledge-transfer artifacts.</li>
<li>Transition mature solutions to the appropriate applications support and operations or enterprise application development, ensuring clear ownership, support readiness, and lifecycle plans.</li>
<li>Monitor deployed solutions for performance, reliability, adoption, model behavior, security concerns, and opportunities for iterative improvement.</li>
<li>Stay current on AI engineering practices, legal-industry AI use cases, emerging tools, AI governance requirements, and applicable technology trends.</li>
<li>Participate in intake prioritization, solution estimation, roadmap planning, vendor evaluations, and innovation portfolio reporting.</li>
<li>Partner with Legal, Risk, Security, and Compliance Teams to ensure AI initiatives meet applicable legal and regulatory obligations.</li>
<li>Ensure AI systems handling client or confidential information meet applicable privacy, security, and data handling requirements across all operating jurisdictions.</li><br>
</ul><div></div><br>
<div><b>KNOWLEDGE:</b>
 </div><ul><li>Experience with Generative AI, Model Context Protocol (MCP), Azure/OpenAI, Large Language Model (LLM), Microsoft CoPilot, prompt engineering, retrieval-augmented generation, embeddings, vector databases, AI agents, model evaluation, and responsible AI practices.</li>
 <li>Application development concepts, including APIs, microservices, web applications, databases, authentication, authorization, logging, monitoring, testing, and CI/CD practices.</li>
 <li>Cloud and enterprise technology environments, including secure API integration, DevOps, identity and access management, data governance, and application lifecycle management.</li>
 <li>Automation and orchestration technologies, such as workflow platforms, robotic process automation, low-code/no-code development tools, and integration platforms.</li>
 <li>Data privacy, confidentiality, information security, records retention, and risk considerations applicable to professional-services or legal environments.</li>
 <li>Software development methodologies, including Agile, Kanban, rapid prototyping, product discovery, and iterative delivery.</li>
 <li>Legal-industry workflows and systems is preferred, including document management, knowledge management, time and billing, matter management, legal research, e-discovery, client intake, and financial systems.</li>
</ul><div><b>SKILLS:</b>
</div><ul><li>Strong software engineering skills in one or more modern programming languages, such as Python, JavaScript/TypeScript, C#, ASP.NET Core, SQL, or similar technologies.</li>
<li>Ability to build and deploy AI-enabled applications using APIs, SDKs, orchestration frameworks, cloud services, and enterprise platforms.</li>
<li>Ability to translate ambiguous business needs into clearly defined user stories, technical requirements, solution designs, and delivery plans.</li>
<li>Strong consultative and communication skills, with the ability to work effectively with attorneys, senior business leaders, technical teams, vendors, and nontechnical users.</li>
<li>Ability to explain AI capabilities, limitations, risks, and recommended controls in clear, practical language.</li>
<li>Strong analytical, problem-solving, and systems-thinking abilities.</li>
<li>Ability to balance speed and experimentation with security, quality, governance, maintainability, and long-term supportability.</li>
<li>Experience designing user-centered solutions and incorporating feedback into rapid iterations.</li>
<li>Strong organization and prioritization skills in a fast-moving environment with multiple concurrent initiatives.</li>
<li>Knowledge of responsible AI frameworks such as React and emerging international AI regulations.</li>
</ul><div><b>INTERESTS:</b>
</div><ul><li>Genuine curiosity about applying AI to meaningful legal, client-service, and business-operations challenges.</li>
<li>Interest in working directly with end users and seeing solutions through from discovery to measurable adoption.</li>
<li>Interest in responsible AI, data protection, human-centered design, and practical technology governance.</li>
<li>Enthusiasm for experimentation, continuous learning, emerging technologies, and building reusable enterprise capabilities.</li>
<li>Interest in improving how attorneys and professional-services teams access knowledge, complete work, collaborate, and serve clients.</li>
 </ul><div></div><div><b>EDUCATION AND EXPERIENCE:</b>
</div><div></div><ul><li>Bachelor&rsquo;s degree in Computer Science, Software Engineering, Information Systems, Data Science, Artificial Intelligence, or a related technical discipline required; equivalent combination of education, training, and relevant experience may be considered.</li>
<li>Minimum of 5 years of experience in software engineering, application development, automation, systems integration, data engineering, or related technical roles.</li>
<li>Minimum of 2 years of experience designing, developing, or deploying AI-enabled, machine-learning, generative AI, automation, or intelligent workflow solutions preferred.</li>
<li>Experience building applications using large language model APIs, RAG architectures, AI orchestration frameworks, Model Context Protocol (MCP), Azure/OpenAI, vector search technologies, or agentic workflow patterns strongly preferred.</li>
<li>Experience with cloud platforms such as Microsoft Azure or Amazon Web Services⁠.</li>
<li>Experience with enterprise integrations, APIs, identity and access management, secure development practices, and application lifecycle management required.</li>
<li>Experience in a law firm, legal technology provider, consulting firm, financial-services organization, or other regulated professional-services environment strongly preferred.</li>
<li>Experience working with cross-functional stakeholders and delivering technology solutions from discovery through production deployment required.</li>
<li>Relevant certifications in cloud engineering, AI, software development, security, automation, Agile delivery, or legal technology are preferred but not required.</li></ul></div></div></div></div></div></div></div></div><div></div>

Wight & Company

<div><p>Are you looking for an opportunity to do challenging, creative work that makes a real impact? Would you like to be part of a company that respects individual contributions and thrives on collaboration? Do you love to win? Then consider joining Wight &amp; Company. We're a nationally recognized, award-winning architecture, engineering, and construction firm known for a dynamic company culture that fosters innovation and challenges the status quo, and we're looking for a talented professional to join our team.</p>
<p>
Wight &amp; Company is seeking an <b>AI Solutions &amp; Data Engineer</b> to help turn artificial intelligence and organizational data into practical solutions for our teams, clients, and projects. This <b>hybrid</b> role will work across architecture, engineering, construction, and business operations to identify valuable AI opportunities, develop AI agents and automated workflows, connect information from multiple systems, and help employees confidently apply AI in their work. The ideal candidate combines technical ability with curiosity, creativity, and strong communication skills. This person should be comfortable building solutions directly, facilitating conversations with teams, translating business challenges into technical approaches, and teaching others how to use new tools effectively. The AI Solutions &amp; Data Engineer will report to the Chief Innovation Officer and collaborate with technology, BIM, operations, and departmental leaders across the company.</p>
<p><b>
ESSENTIAL RESPONSIBILITIES</b></p>
<p><b>
Develop AI Solutions and Agents</b></p>
<ul>
<li>Design, build, test, and maintain AI agents that support project delivery and business operations.</li>
<li>Develop solutions using large language models, retrieval-augmented generation, workflow automation, APIs, and related technologies.</li>
<li>Connect AI tools with internal applications, document repositories, databases, and third-party platforms.</li>
<li>Create prototypes and pilot programs that allow teams to evaluate new ideas quickly.</li>
<li>Establish methods for testing solution accuracy, reliability, security, and business value.</li>
<li>Help move successful prototypes into maintainable, production-ready solutions.</li>
<li>Monitor the performance and adoption of deployed AI solutions and improve them over time.</li>
</ul>
<p><b>Build and Manage Data Solutions</b></p>
<ul>
<li>Gather, clean, organize, and combine data from multiple business and project systems.</li>
<li>Develop and maintain data pipelines, integrations, structured datasets, and reusable data services.</li>
<li>Help establish reliable connections between project, financial, operational, and knowledge-management platforms.</li>
<li>Improve the accessibility and usefulness of organizational data while maintaining appropriate security and permissions.</li>
<li>Collaborate with system owners to improve data quality, consistency, documentation, and governance.</li>
<li>Support dashboards, reporting, predictive analytics, and AI applications that depend on reliable data.</li>
<li>Identify opportunities to reduce duplicate data entry and improve the flow of information across the organization.</li>
</ul>
<p><b>Identify and Prioritize AI Opportunities</b></p>
<ul>
<li>Meet with teams across the company to understand their work, challenges, and opportunities.</li>
<li>Facilitate workshops and brainstorming sessions focused on meaningful business problems rather than technology alone.</li>
<li>Translate business needs into clearly defined AI, automation, or data initiatives.</li>
<li>Evaluate potential solutions based on value, feasibility, risk, scalability, and alignment with company priorities.</li>
<li>Help departments develop practical roadmaps for adopting AI and improving their use of data.</li>
<li>Stay informed about emerging AI capabilities and evaluate where they may create value for the company or its clients.</li>
</ul>
<p><b>Train and Support Teams</b></p>
<ul>
<li>Develop and deliver practical AI training for employees with varying levels of technical experience.</li>
<li>Teach teams how to use approved AI tools effectively, securely, and responsibly.</li>
<li>Create guides, demonstrations, templates, prompt libraries, and other reusable learning resources.</li>
<li>Coach individuals and teams as they incorporate AI into existing workflows.</li>
<li>Support a network of internal AI champions who can help expand adoption across the organization.</li>
<li>Share successful use cases and lessons learned to encourage continuous improvement.</li>
</ul>
<p><b>Support Responsible AI and Data Governance</b></p>
<ul>
<li>Help establish technical standards for AI development, data integration, documentation, testing, and deployment.</li>
<li>Apply appropriate security, privacy, intellectual-property, and data-governance requirements to AI solutions.</li>
<li>Work with technology, legal, risk, and business leaders to evaluate proposed tools and use cases.</li>
<li>Maintain clear documentation of data sources, integrations, models, prompts, permissions, dependencies, and system behavior.</li>
<li>Promote responsible human oversight and clearly communicate the limitations of AI-generated results.</li>
</ul>
<p><b>BACKGROUND &amp; EXPERIENCE EXPECTATIONS</b></p>
<ul>
<li>Bachelor's degree in computer science, data engineering, information systems, software engineering, or a related field&mdash;or equivalent professional experience.</li>
<li>Experience developing AI-enabled applications, software integrations, data solutions, or workflow automations.</li>
<li>Proficiency in Python, SQL, APIs, and common data-processing methods.</li>
<li>Experience working with structured and unstructured data from multiple sources.</li>
<li>Understanding of modern generative AI concepts, including large language models, embeddings, vector search, tool use, and retrieval-augmented generation.</li>
<li>Experience developing with cloud platforms, databases, automation tools, or enterprise application ecosystems.</li>
<li>Ability to translate loosely defined business challenges into practical technical solutions.</li>
<li>Strong written, verbal, presentation, and facilitation skills.</li>
<li>Ability to explain technical concepts clearly to nontechnical audiences.</li>
<li>A collaborative mindset and an interest in working directly with employees across many disciplines.</li>
<li>Sound judgment regarding data privacy, cybersecurity, intellectual property, and responsible AI use.</li>
<li>Ability to balance experimentation and speed with reliability, documentation, and long-term maintainability.</li>
</ul>
<p><b>PREFERRED QUALIFICATIONS</b></p>
<ul>
<li>Experience with Microsoft Azure, Microsoft 365, Copilot Studio, Power Platform, Fabric, or related Microsoft technologies.</li>
<li>Experience with AI platforms and APIs such as Azure OpenAI, OpenAI, Anthropic, or similar services.</li>
<li>Experience with ETL/ELT processes, data warehouses, lakehouses, semantic models, or business-intelligence platforms.</li>
<li>Familiarity with agent frameworks, orchestration tools, vector databases, or enterprise search technologies.</li>
<li>Experience with application development, source control, testing, deployment, and DevOps practices.</li>
<li>Experience delivering technical training, facilitating workshops, or supporting organizational change.</li>
<li>Familiarity with architecture, engineering, construction, professional services, or project-based organizations.</li>
<li>Experience integrating enterprise systems such as Microsoft 365, Autodesk Construction Cloud, Procore, Bentley, Unanet, CMiC, Egnyte, or similar platforms.</li>
<li>Familiarity with BIM, digital project delivery, estimating, construction management, or design technology is beneficial but not required.</li>
</ul>
<p><b>Salary Range</b>: $100,000 - $160,000. Individual pay will be based on several factors including experience, knowledge, skills, and abilities of the applicant.</p>
<p>
Wight &amp; Company offers excellent benefits and a wonderful work environment. Our comprehensive benefits including medical, dental, vision, disability, life insurance, flexible spending, paid holidays, paid time off, and a 401(k). Our flexible work schedule allows for a healthy work-life balance. For more information about our company, visit our website at www.wightco.com.</p>
<p>
Wight &amp; Company is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetics, protected veteran status, disability status, or any other characteristic protected by federal, state, or local laws.</p>
<p>
Wight &amp; Company values diversity in our workforce. We are committed to recruiting, hiring, and promoting people with disabilities and veterans. If you need an accommodation to assist with completing the electronic application, please call us at 630.969.7000 and ask to speak with a Human Resources representative.</p>
<p>
#LI-NS1</p></div><p></p>

AI Solutions & Data Engineer

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