Senior Software Engineer (Tech Lead) responsible for end-to-end software engineering excellence across Cisco EAIPI’s flagship AI platforms, leading feature roadmaps, architectural design, and production operations.
Responsibilities
Lead technical design and implementation of AI platform features
Own feature roadmaps and deliverables
Conduct code reviews and enforce quality standards
Optimize performance and scalability of distributed systems
Ensure secure architecture and threat modeling
Requirements
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related STEM field
Lead the design, development, and deployment of innovative enterprise AI solutions that transform business operations and decision-making.
Compensation
Competitive compensation: Salary and compensation details are not specified in the available job description.
Responsibilities
Design, develop, operationalize, and deploy AI, machine learning, and large language model (LLM)-based solutions in production environments.
Define and implement scalable AI architecture patterns covering data ingestion, model integration, model tuning, orchestration, and application layers.
Design, build, and optimize data pipelines and integrations that support enterprise AI use cases.
Partner with operational technology (OT), IT, and data engineering teams to integrate manufacturing and industrial data.
Lead the implementation of enterprise copilots, including Microsoft Copilot and custom GPT-based applications.
Requirements
Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or a related discipline, or equivalent practical experience
Senior AI Engineer to design, build, and deploy advanced AI-powered applications for a major US financial services client, focusing on extracting business and technical requirements from legacy codebases and documentation.
Responsibilities
Lead the end-to-end development of AI-powered solutions, from architecture and technical design to implementation, testing, and production deployment, using an agentic SDLC approach.
Design and build agentic AI architectures, including LLM integrations through APIs, Retrieval-Augmented Generation (RAG), tool orchestration, runtime frameworks, system prompts, and safety guardrails.
Develop and maintain context data pipelines using internal data sources and vector databases to provide AI agents with reliable, relevant, and high-quality information.
Build backend services and APIs using Python and develop user-facing applications with React.
Create, customize, and share reusable AI development assets, including agents, skills, subagents, commands, and development harnesses, to improve engineering productivity.
Requirements
Nice to have: COBOL
Nice to have: Java
Nice to have: .NET
Nice to have: knowledge graphs
Nice to have: LLM observability and evaluation tools
Seeking a technically skilled AI Developer to design and build intelligent applications that enhance business processes and automate workflows using LLMs and generative AI technologies.
Responsibilities
Design, develop, and deploy AI-powered applications and solutions.
Integrate Large Language Models (LLMs) and generative AI tools into existing products and systems.
Build AI agents, chatbots, and automated workflows to streamline business processes.
Work with APIs and third-party AI platforms to introduce intelligent functionalities.
Implement Retrieval-Augmented Generation (RAG) architectures and integrate vector databases.
Seeking a technically skilled AI Developer to design and build intelligent applications that enhance business processes and automate workflows using large language models, generative AI technologies, and machine learning tools.
Responsibilities
Design, develop, and deploy AI-powered applications and solutions
Integrate Large Language Models (LLMs) and generative AI tools into existing products and systems
Build AI agents, chatbots, and automated workflows to streamline business processes
Work with APIs and third-party AI platforms to introduce intelligent functionalities
Implement Retrieval-Augmented Generation (RAG) architectures and integrate vector databases
Seeking a technically skilled AI Developer to design and build intelligent applications that enhance business processes and automate workflows using large language models and generative AI technologies.
Responsibilities
Design, develop, and deploy AI-powered applications and solutions
Integrate Large Language Models (LLMs) and generative AI tools into existing products and systems
Build AI agents, chatbots, and automated workflows to streamline business processes
Work with APIs and third-party AI platforms to introduce intelligent functionalities
Implement Retrieval-Augmented Generation (RAG) architectures and integrate vector databases
Act as a trusted technical advisor and hands-on engineering expert, helping enterprise customers design, implement, and scale advanced agentic AI solutions.
Compensation
Competitive compensation: Attractive remuneration package aligned with your skills and professional experience.
Responsibilities
Own the technical success of enterprise customers' agentic AI initiatives, managing the complete delivery lifecycle from initial discovery and solution design through development, production deployment, ongoing operations, and advisory services.
Lead customer workshops to identify, assess, and prioritize high-value agentic AI use cases, translating business objectives into measurable and technically achievable workflows.
Design and implement sophisticated multi-agent architectures, including agent decomposition, orchestration, task delegation, tool integration, memory management, state handling, and human-in-the-loop controls.
Develop, review, and troubleshoot production-quality software using Go or Python, building agents, plugins, tools, and integrations that meet enterprise requirements.
Deploy and operate agentic AI applications using Docker, Kubernetes, and major cloud platforms, ensuring scalability, reliability, and maintainability.
Requirements
Professional fluency in English and either Spanish or Italian
Act as a trusted technical advisor and hands-on engineering expert, helping enterprise customers design, implement, and scale advanced agentic AI solutions.
Compensation
Competitive compensation: Attractive remuneration package aligned with your skills and professional experience.
Responsibilities
Own the technical success of enterprise customers' agentic AI initiatives, managing the complete delivery lifecycle from initial discovery and solution design through development, production deployment, ongoing operations, and advisory services.
Lead customer workshops to identify, assess, and prioritize high-value agentic AI use cases, translating business objectives into measurable and technically achievable workflows.
Design and implement sophisticated multi-agent architectures, including agent decomposition, orchestration, task delegation, tool integration, memory management, state handling, and human-in-the-loop controls.
Develop, review, and troubleshoot production-quality software using Go or Python, building agents, plugins, tools, and integrations that meet enterprise requirements.
Deploy and operate agentic AI applications using Docker, Kubernetes, and major cloud platforms, ensuring scalability, reliability, and maintainability.
Requirements
Relevant certifications, such as AWS Certified Machine Learning or Generative AI, Azure AI Engineer Associate, or Google Professional Machine Learning Engineer
Act as a trusted technical advisor and hands-on engineering expert, helping enterprise customers design, implement, and scale advanced agentic AI solutions.
Compensation
Competitive compensation: Attractive remuneration package aligned with your skills and professional experience.
Responsibilities
Own the technical success of enterprise customers' agentic AI initiatives, managing the complete delivery lifecycle from initial discovery and solution design through development, production deployment, ongoing operations, and advisory services.
Lead customer workshops to identify, assess, and prioritize high-value agentic AI use cases, translating business objectives into measurable and technically achievable workflows.
Design and implement sophisticated multi-agent architectures, including agent decomposition, orchestration, task delegation, tool integration, memory management, state handling, and human-in-the-loop controls.
Develop, review, and troubleshoot production-quality software using Go or Python, building agents, plugins, tools, and integrations that meet enterprise requirements.
Deploy and operate agentic AI applications using Docker, Kubernetes, and major cloud platforms, ensuring scalability, reliability, and maintainability.
Requirements
Relevant certifications, such as AWS Certified Machine Learning or Generative AI, Azure AI Engineer Associate, or Google Professional Machine Learning Engineer
Software EngineerNewCisco · Bangalore, India
AI Solutions ArchitectNewJobgether · Remote, US