Top Tech Jobs & Startup Jobs

Design, develop, deploy, and support production-grade Generative AI applications. Build RAG pipelines, LLM workflows, AI agents, backend APIs, responsive frontends, database and vector-search integrations, and cloud deployments. Own solutions from design through production, including authentication, monitoring, security, performance optimization, troubleshooting, and quality improvements. Collaborate with product, data, AI, and business teams to deliver enterprise applications.

Develop scalable full-stack web applications using Python, React or Next.js, PostgreSQL, and REST APIs. Responsibilities include backend and frontend development, database optimization, performance and reliability improvements, troubleshooting, testing, code reviews, and collaboration with product, design, and engineering teams in an Agile/Scrum environment.

Perform functional, integration, regression, and end-to-end testing for data and AI/ML applications. Validate data quality, transformations, ETL/ELT pipelines, model predictions, and data integrity using SQL and Python. Design test cases, automate testing, track defects, and collaborate with data engineers, data scientists, ML engineers, and development teams. Test model accuracy, performance, consistency, and reliability while supporting API, CI/CD, and data platform testing.

Leads enterprise supply chain consulting engagements across manufacturing, life sciences, and pharmaceutical industries. Facilitates discovery workshops, assesses business processes, defines SAP-based transformation solutions, and advises on demand and supply planning, inventory optimization, manufacturing operations, regulatory compliance, data models, and AI-enabled modernization. Collaborates with business stakeholders, architects, data teams, and engineers to translate complex supply chain requirements into scalable digital solutions.

Design and lead enterprise-scale AI, machine learning, and Generative AI solutions from architecture through deployment. Build data pipelines, feature engineering frameworks, RAG applications, AI agents, and LLM-powered systems. Establish MLOps practices for versioning, experimentation, monitoring, and CI/CD. Partner with stakeholders on AI initiatives, ensure security and governance compliance, and mentor ML engineers, data scientists, and AI teams.

Lead client-facing delivery of AI and data solutions involving LLMs, generative AI, RAG pipelines, cloud platforms, and data architectures. Independently run discovery, scope deliverables, review technical outputs, create SOWs and proposals, present to senior stakeholders, and own delivery outcomes across multiple workstreams. The role emphasizes technical understanding, rapid prototyping, consulting, and embedded client delivery rather than production coding.

Assists with developing and testing AI/ML models, collecting and preprocessing data, implementing machine learning, NLP, or computer vision algorithms, collaborating on AI-driven solutions, documenting project outcomes, and staying current with AI/ML trends.