At Leidos, you'll contribute to AI solutions that serve critical national and global missions—ranging from defense and intelligence to healthcare, energy, and space exploration. Our work emphasizes Trusted Mission AI: systems that are transparent, ethical, resilient, and accountable. You’ll collaborate with multidisciplinary teams to transition AI research into operational environments where accuracy, security, and reliability are non-negotiable. Joining Leidos means applying your expertise to solve some of the most complex and meaningful challenges of our time. We are looking for a motivated AI engineer who wants to work on challenging problems in a variety of domains – including enterprise IT, health, defense, intelligence, and energy – to get results that apply and go beyond the state of the art for measurably better outcomes. We apply our knowledge, capabilities, and experience to develop and deploy Trusted Mission AI – AI that deserves to be trusted by system owners, end users, and the public – to be helpful, harmless, and honest. We are looking for a researcher that is expert in envisioning, developing, and securing AI agents using generative AI and LLM-based tools to transform and add value to human workflows. Primary Responsibilities The AI Engineer will collaborate with Agentic AI Scientists to build and deploy AI agents to both automate and optimize labor intensive workflows, as well as empowering the human workforce to discover entirely new capabilities. As a member of the Leidos AI Accelerator, they will be tasked at different times with both R&D as well as customer-facing goals, to speed the transition of novel applied research and solutions development into impact on contract. The tasks of the AI Engineer will include creating software to support AI agent communication, connecting models and agents to external services via API calls, testing and debugging tasks, deploying into target environments, setting up monitoring, and ensuring reliable execution of agentic AI systems. They will utilize a combination of open-source models, agentic tools, and large proprietary commercial models. They will be developing novel approaches to securing agentic workflows and to evaluating the results for accuracy, performance, and impact. They will be expected to ensure AI systems adhere to ethical guidelines, transparency, and fairness principles. They should expect they may conduct research, develop prototypes, evaluate and document results, potentially through publication and presentation at conferences and other public forums. They should also expect they may be part of a team developing solutions for deployment into operational environments, or for integration into mission systems. They should be a self-starter while also working well within the team, collaborating and sharing discoveries and seeking feedback. Multiple openings at various levels. The various position’s minimum education and experience requirements are as follows: - T1: Bachelor's degree in Computer Science, Engineering or related field and relevant experience - T2: Bachelor's degree in Computer Science, Engineering or related field and 2+ years of relevant experience, or a Masters degree with relevant experience - T3: Bachelor's degree in Computer Science, Engineering or related field and 4+ years of directly applicable experience, or a Masters degree and 2+ years of directly applicable experience Basic Qualifications - Self-starter with a high degree of intellectual curiosity - Proficiency in applying technical principles, theories, and concepts in the field - Experience developing Agentic AI solutions, including autonomous planning–execution–reflection loops, multi-agent collaboration and coordination, and tool usage patterns including API integration, retrieval-augmented generation (RAG), and memory/context management - Solid understanding and hands-on experience with generative AI models including prompt engineering, chain-of-thought reasoning, and Natural Language Processing (NLP) tasks such as entity extraction, summarization, and semantic search. - Ability to effectively guide junior engineers in applying standard practices and resolving problems of moderate complexity - Working knowledge of Large Language Models (LLMs) and agent frameworks such as LangChain, LangGraph, CrewAI, A2A, MCP, or AutoGen - Experience using vector databases (e.g., Pinecone, Weaviate, FAISS) - Proficiency in modern software languages—preferably, Python - Experience with the Software Development Lifecycle (SDLC), including DevSecOps practices - Familiarity with deployment into virtualized and containerized environments (e.g., VMware, Docker, Kubernetes) - Ability to obtain a Secret clearance Preferred Qualifications - Experience designing and implementing safety, guardrails, and bias-mitigation strategies for autonomous agents and multiagent systems - Experience integrating agents with cloud-native workflows, streaming data pipelines, and real-time decision-making environments - Familiarity with evaluation and observability tools for AI agents, such as LangSmith, OpenAI Evals, or custom telemetry systems - Experience with AI service integration such as NIMS, Azure OpenAI, Bedrock, GCP Vertex AI - Proficiency in scripting with Linux Bash, PowerShell, or equivalent automation tools - Hands-on GPU programming experience for ML workloads using CUDA, PyTorch, or TensorFlow, including optimization for performance and efficiency. If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares. Original Posting: February 6, 2026 For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $69,550.00 - $125,725.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

• Assist in the development and testing of agentic AI systems, including Multi-Agent and Agent-to-Agent (A2A) workflows, leveraging common industry standards such as the Model Context Protocol (MCP) to create interoperable AI agents. • Support the implementation of MCP Tools and Resources that enable Large Language Models (LLMs) to interact with internal systems and APIs in a secure, standardized manner. • Collaborate with engineers and data scientists to contribute to the architecture of a centralized "AI Gateway" that provides a unified, platform-independent interface for leveraging various LLMs. • Help implement observability pipelines to track trace-level data, monitor model latency, and support the optimization of Generative AI systems in production. • Work closely with senior team members to translate strategic designs into functional, production-ready solution components. • Participate in the implementation of AI guardrails to filter inputs and outputs, supporting data security, integrity, and the prevention of adversarial attacks such as prompt injection. • Assist in the design and implementation of Retrieval-Augmented Generation (RAG) pipelines to enhance LLM accuracy and grounding with enterprise data sources. • Learn and apply engineering best practices including version control (Git), automated testing, and CI/CD processes for AI systems. • Stay current with emerging trends in agentic AI, operational AI, and MLOps, and contribute ideas to continuously evolve the team's capabilities.

Do you want to join a team where the mission is meaningful, the challenges are complex, and you can directly see the results of your hard work? Lundbeck is a global biopharmaceutical company focusing exclusively on brain health. With more than 70 years of experience in neuroscience, we are committed to improving the lives of people with neurological and psychiatric diseases. Lundbeck employees are inspired and driven by our purpose to advance brain health and transform lives. Join us on our journey of growth! Remote opportunity - Open to candidates anywhere in the greater United States SUMMARY: We are seeking a highly skilled and forward-thinking AI Engineer to design, develop, and scale generative AI solutions across the organization. This role will play a critical part in translating emerging AI capabilities into enterprise-grade applications that drive business value, operational efficiency, and innovation. You will work cross-functionally with data scientists, IT, compliance, and business stakeholders to deliver secure, scalable, and production-ready AI solutions. ESSENTIAL FUNCTIONS: - Design, build, and deploy scalable GenAI applications leveraging LLMs, RAG architectures, and foundation models. - Develop and optimize advanced retrieval and context engineering strategies using internal knowledge bases and structured/unstructured data. - Design and orchestrate multi-step AI agents capable of reasoning, retrieval, and action execution across business workflows. - Contribute to enterprise GenAI architecture, ensuring modularity, reusability, scalability, and observability. - Build reusable GenAI components and services (agent frameworks, chat interfaces, orchestration layers, evaluation pipelines). - Integrate AI systems with enterprise platforms (CRM, document management, APIs) using secure authentication and governance standards. - Embed Responsible AI principles including privacy, compliance, auditability, explainability, and risk management. - Continuously evaluate emerging models and tools, benchmark performance, and optimize cost, latency, and system efficiency. REQUIRED EDUCATION, EXPERIENCE, and SKILLS: - Accredited Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. - 3+ years of relevant experience in software engineering, or AI development. - Proven experience developing Generative AI applications, including content generation, conversational AI, and natural language understanding tasks. - Strong proficiency in programming languages such as Python, Java or C++. - Experience with: - REST APIs, - LLM APIs (OpenAI, Azure OpenAI, Anthropic, etc.), - RAG architectures (vector databases such as Pinecone, FAISS, Weaviate, etc.), - LangChain, LlamaIndex, or similar orchestration frameworks, - Cloud platforms (Azure, AWS, or GCP). - Solid understanding of software engineering best practices (CI/CD, version control, testing, documentation). - Knowledge of AI risk, security, and data privacy principles. - Familiarity with AI deployment techniques, including Docker and Kubernetes for scalable production environments. - Strong problem-solving ability to design, develop, and optimize AI applications to meet specific business needs. - Ability to collaborate with cross-functional teams to drive successful deployment and integration of AI solutions. PREFERRED EDUCATION, EXPERIENCE, and SKILLS: - Accredited Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. - Experience deploying AI solutions in regulated production environments. - Experience with model fine-tuning or open-source LLM deployment. - Familiarity with MLOps/LLMOps frameworks. - Understanding of AI governance frameworks and responsible AI principles. - Experience with agent-based systems and multi-step workflows. - Exposure to UI/UX implementation and integration for AI-powered applications. - In-depth experience working with pharmaceutical datasets (first-party patient data, third-party claims, EHR, demand data). - Familiarity with regulatory standards in the pharmaceutical industry (e.g., GxP, ALCOA+). - Strong Preference to be based in Deerfield, IL Office TRAVEL: - Willingness/Ability to travel up to 20% domestically. International travel may be required. - If based remotely, additional travel will be required to Deerfield, IL, to meet the needs of the role and the business The range displayed is a national range, and if selected for this role, may vary based on various factors such as the candidate’s geographical location, qualifications, skills, competencies, and proficiency for the role. Salary Pay Range: $150,000 - $175,000 and eligibility for a 15% bonus target based on company and individual performance, and eligibility to participate in the company’s long-term incentive plan. Benefits for this position include flexible paid time off (PTO), health benefits to include Medical, Dental and Vision, and company match 401k. Additional benefits information can be found on our career site. Applications accepted on an ongoing basis. Why Lundbeck Lundbeck offers a robust and comprehensive benefits package to help employees live well and protect their health, family, and everyday life. Information regarding our benefit offering can be found on the U.S. career site. Lundbeck is committed to working with and providing reasonable accommodations to disabled veterans and other individuals with disabilities during our employment application process. If, because of a disability, you need a reasonable accommodation for any part of the application process, please visit the U.S. career site. Lundbeck is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status, and any other characteristic protected by law, rule, or regulation. Lundbeck participates in E-Verify.

Role Description As a Software Engineer, Artificial Intelligence, you will play a key role in building, operating, and continuously improving AI-driven systems that support internal business capabilities. You will focus on designing and maintaining AI-powered data pipelines, agent-based solutions, and LLM-driven services, working closely with modern data and ML platforms. This role requires strong software engineering foundations combined with hands-on experience in large language models, vector stores, and ML lifecycle management. You will contribute to scalable, production-grade AI solutions while driving quality, reliability, and continuous improvement across the full model and data pipeline lifecycle. - Build and maintain AI-powered data pipelines and extraction processes (batch and streaming) from internal relational data sources and unstructured documents (PDF, Word, PowerPoint) into structured datasets within Databricks. - Own end-to-end delivery of AI solutions, from design through production. - Design and manage text embeddings and vector stores within Databricks for use with vector indexing and retrieval solutions. - Drive architecture and best practices for AI-powered systems. - Design, develop, and maintain custom tools implemented as MCP servers and Databricks applications to extend agent and model capabilities. - Design, develop and implement AI Agents using frameworks like LangChain and LangGraph. - Implement LLM scorers to validate and monitor agents, applications and models. Prevent issues like hallucinations or unnecessary actions through structured testing and guardrails. - Drive continuous improvement through prompt engineering, pipeline optimization, vector store tuning, and scorer refinement to ensure high-quality LLM responses. - Collaborate on production deployments, monitoring, and scalability of ML and LLM-based services. Qualifications - 5-8 years of industry experience in software engineering or related roles. - Strong proficiency in Python, including production services, asynchronous programming, and testing. - Hands-on experience with AI Agents Development frameworks such as LangChain, LangGraph and LlamaIndex. - Experience using MLflow for prompt engineering, experimentation, evaluation, model registry, and deployments. - Solid understanding of vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma or similar), including serverless or managed options. - Experience implementing Retrieval augmented generation (RAG) solutions. Data Ingestion and Retrieval, LLM Generation. - Experience building and consuming REST APIs, model serving solutions, and CI/CD pipelines. - Experience working with cloud platforms (AWS), containerization (Docker), and modern deployment practices. - Hands-on experience with Databricks, Apache Spark, and Delta Lake (nice to have). - Advanced English level, both written and verbal.