5 Llm Integration Jobs

Sr Applications Developer - (Full Stack Developer - AI Engineering Practice) BMC is looking for an experienced Full Stack Developer to join our team working on building and maintaining our Generative AI engineering and research platform. This position involves working with advanced AI technologies, balancing practical engineering implementation with innovative AI solutions, and ensuring code quality and functionality in our AI applications. Here is how, through this exciting role, YOU will contribute to BMC's and your own success: Design and develop full-stack applications using React (frontend) and Fast API (backend) Build and optimize LLM applications using Langchain and related frameworks Architect and maintain cloud-native applications on AWS EKS clusters Implement and optimize integrations with Bedrock services for LLM functionalities Develop and maintain AI pipelines using Python ML frameworks Manage and optimize databases (ex. PostgreSQL) in AWS RDS Integrate and maintain SSO solutions using OKTA Collaborate with AI researchers to implement and deploy ML models Design and develop RESTful APIs for AI service integration Implement secure and scalable cloud infrastructure using AWS services Lead technical design discussions and architecture reviews To ensure youre set up for success, you will bring the following skillset & experience: 5+ years of full-stack development experience Strong proficiency in React.js and modern JavaScript/TypeScript Expert-level Python development skills Experience with Python AI/ML frameworks: Langchain for LLM applications NumPy and Pandas for data manipulation Scikit-learn for ML implementations PyTorch or TensorFlow (preferred) Experience with Fast API framework Proven experience with AWS services, especially EKS and RDS Solid understanding of Kubernetes and container orchestration Experience with PostgreSQL and database optimization Knowledge of authentication systems and SSO implementation (OKTA preferred) Experience with CI/CD pipelines and DevOps practices Understanding of RESTful API design principles Whilst these are nice to have, our team can help you develop in the following skills: Experience with LLM integration and AI services Familiarity with AWS Bedrock or similar AI services Strong background in Python ecosystem: Hugging Face transformers Streamlet for AI applications Experience with vector databases (e.g., Pinecone, Chroma) Experience in prompt engineering and LLM optimization techniques Experience in implementing microservices architecture Experience with monitoring and observability tools Security best practices in cloud environments The ideal candidate will demonstrate full stack proficiency via past work samples, GitHub projects, whiteboarding sessions and a potential live coding test

Role Overview: We are looking BI + data-engineer kind of skills. The main work is to design & build complex Tableau dashboards, set up robust automated data pipelines and backend tables and do this in an optimized manner. There is also LLM integration into the dashboard, which will require some initiative and exploration. Automations + LLM integration would require some Python experience Job Description: Requirements 3+5 Years of experience in a product analytics, data analyst, or analytics product role Hands on experience in advanced SQL, python Advanced Tableau experience (Min 2yrs hands on experience in Tableau mandatory) Experience in LLM integration into the dashboard • Proven ability to support and improve analytical products that drive business decisions Roles and Responsibilities: Product Thinking & Ownership Product development exposure : Experience working on analytics or data products throughout the product lifecycle - from requirements to delivery. Prioritization skills : Can independently manage a backlog, help triage requests and contribute to roadmap planning. Analytical & Technical Proficiency Strong SQL skills : Can write and optimize queries to explore data and validate product behavior or outcomes. Data visualization : Comfortable building dashboards or reports in tools like Tableau Cross-functional skills : Experience working with product managers, analysts, and engineers to drive product outcomes. Comfort with data pipelines : Understands how data flows through systems; collaborates effectively with data engineers and analytics teams. Model consumption : Understands the basics of AI/ML model outputs and how they feed into products

Lead full product lifecycle: strategy launch iteration Define vision, roadmap and success metrics Collaborate with Engineering, Design, QA, and Marketing Leverage Gen AI, LLMs, and data modeling Proficient in Jira, Confluence, Figma, and SQL

Experience: 10 Years Work Type: Onsite Budget: As per market standards Primary Skills NodeJS 6+ years of hands-on backend development JavaScript / HTML / CSS Strong frontend development capabilities ReactJS / VueJS Working knowledge or project experience preferred AWS Serverless Architecture Mandatory (Lambda, API Gateway, S3) LLM Integration / AI Development Experience with OpenAI, Anthropic APIs Prompt Engineering Context management and token optimization SQL / NoSQL Databases Solid experience with relational & non-relational DBs EndToEnd Deployment Deploy, debug, and manage full-stack apps Clean Code Writes clean, maintainable, production-ready code Secondary Skills Amazon Bedrock Familiarity is a strong plus Web Servers Experience with Nginx / Apache configuration RAG Patterns / VectorDBs / AIAgents Bonus experience Software Engineering Best Practices Strong design & architecture skills CI/CD / DevOps Exposure Beneficial for full pipeline integration Expectations Own frontend and backend development Collaborate closely with engineering and client teams Build scalable, secure, and intelligent systems Influence architecture and tech stack decisions Stay up-to-date with AI trends and serverless best practices

Job Summary: We are seeking an experienced and forward-thinking AI Subject Matter Expert (SME) to lead the design, development, and integration of custom and commercial AI solutions. The ideal candidate will bring deep technical expertise, a passion for innovation, and a strategic mindset to drive impactful AI initiatives across the organization. Key Responsibilities: Custom AI Development: Design, build, and deploy tailored AI models and solutions that address specific business challenges and objectives. Commercial AI Integration: Evaluate, recommend, and implement commercial AI platforms and tools to enhance operational efficiency and business outcomes. Research & Innovation: Stay abreast of emerging AI technologies, trends, and research; identify opportunities to innovate and apply cutting-edge techniques. Advanced Data Analysis: Analyze complex datasets to uncover patterns, support model development, and inform decision-making. Cross-functional Collaboration: Partner with data scientists, software engineers, analysts, and business stakeholders to ensure seamless integration of AI solutions. Documentation & Knowledge Sharing: Create thorough documentation of models, algorithms, and development processes; contribute to organizational knowledge bases. Training & Support: Mentor team members and provide training sessions for stakeholders to build AI literacy and adoption across teams. Qualifications Education: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience: 6-9 years of hands-on experience in AI solution development and implementation, with a strong portfolio of successful projects . Technical Proficiency: Expertise in AI/ML frameworks such as TensorFlow, PyTorch, Keras. Strong programming skills in Python (preferred), R, and experience with data tools such as SQL and Pandas. Familiarity with deploying models in production environments . Analytical & Problem-Solving Skills: Ability to interpret complex data, design intelligent systems, and develop actionable insights . Communication: Strong written and verbal communication skills, capable of translating complex concepts for non-technical audiences . Project Management: Demonstrated ability to lead AI projects end-to-end from planning to deployment and performance monitoring . Adaptability: Comfortable working in a dynamic, fast-paced environment with evolving business needs.