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Job Summary

Equinix is seeking a highly motivated Senior Software Engineer with a strong focus on building AI/ML‑driven solutions to join our Bangalore team. In this role, you will design, build, and launch production‑grade, multi‑agent systems and conversational experiences, spanning orchestration, RAG design, model serving, real‑time inference, and observability. You will work with state‑of‑the‑art Large Language Models (LLMs), agentic AI frameworks, and modern engineering practices to deliver solutions that meet real customer and business needs.

As a Senior Software Engineer, you will own the AI roadmap, serve as the primary technical subject‑matter expert, and collaborate closely with IT, security, and business teams to deliver secure, compliant, and highly scalable AI solutions. This role offers the opportunity to shape how AI is adopted and operationalized across the organization.

This position is ideal for someone passionate about applying cutting‑edge AI technologies (such as GPT, Claude, and LLaMA) to real‑world problems, with strong engineering fundamentals and product intuition. You will work at the intersection of AI reasoning, automation, and user experience, building intelligent agents capable of decision‑making, context retention, and multi‑step task execution.

Responsibilities

• Design, build, and own production‑grade Agentic AI systems using frameworks such as OpenAI, LangChain, LlamaIndex, AutoGen, CrewAI, Google ADK, or similar platforms, with a focus on scalability, reliability, and maintainability

• Architect and develop conversational AI assistants and intelligent agents across multiple channels (chat, APIs, embedded applications), ensuring seamless user experiences and enterprise readiness

• Integrate Large Language Models (OpenAI, Anthropic, Gemini, etc.) with APIs, databases, vector stores, and enterprise systems to enable end‑to‑end AI‑driven workflows

• Design and implement memory, retrieval, planning, and reasoning components to build goal‑oriented, context‑aware agents capable of multi‑step decision making.

• Apply and optimize advanced prompting strategies (prompt engineering, chain‑of‑thought reasoning, tool use, and agent orchestration) to improve accuracy, reliability, latency, and cost efficiency

• Lead the design and adoption of RAG (Retrieval‑Augmented Generation) architectures, ensuring high factual accuracy, relevance, and traceability across enterprise knowledge sources

• Establish evaluation frameworks for AI systems, including offline and online metrics, hallucination detection, regression testing, guardrails, and human‑in‑the‑loop feedback mechanisms

• Operationalize AI systems in production, including monitoring, logging, observability, cost controls, and continuous improvement using feedback loops and performance analytics

• Build and maintain LLMOps / MLOps pipelines, covering model versioning, experimentation, deployment, rollback strategies, and environment promotion

• Ensure security, privacy, and ethical AI practices by implementing data protection, prompt and output safeguards, policy enforcement, and compliance with enterprise standards

• Collaborate closely with Product Managers, business stakeholders, and cross‑functional teams to translate business objectives into AI‑driven solutions with measurable impact

• Conduct feasibility assessments and develop proofs‑of‑concept, validating emerging AI approaches, tools, and architectures before production adoption

• Stay ahead of emerging AI technologies and trends, proactively identifying opportunities for automation, efficiency gains, and AI‑powered enhancements

• Own technical decision‑making and architecture tradeoffs, balancing performance, scalability, security, and cost in enterprise environments

• Mentor junior engineers and guide technical best practices, while educating non‑technical stakeholders on AI capabilities, limitations, and responsible use.

• Contribute to engineering excellence by defining standards, documenting architectures, and fostering a collaborative, high‑performance team culture

Qualifications

Required

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience

• 5+ years of strong software engineering experience with proficiency in Python and familiarity with JavaScript / TypeScript or similar languages

• 2+ years of hands‑on experience building solutions using Agentic AI and LLM frameworks such as OpenAI, Hugging Face, LangChain, LlamaIndex, AutoGen, CrewAI, or Semantic Kernel

• Strong understanding of software engineering best practices, including version control, CI/CD pipelines, automated testing, and code review

• Experience with cloud platforms (AWS, GCP, or Azure) and modern deployment practices, including Docker and Kubernetes

• Proficiency working with vector databases and embedding systems such as Pinecone, FAISS, Weaviate, Chroma, or Milvus

• Demonstrated experience building, deploying, and maintaining generative AI applications in production environments

• Solid background in NLP, machine learning, including model training, fine‑tuning, or evaluation techniques

• Experience designing and implementing multi‑agent systems, autonomous workflows, or AI‑driven orchestration pipelines

• Understanding of LLM performance considerations, including latency, cost optimization, prompt reliability, and evaluation

• Awareness of AI security, data privacy, and responsible AI principles in enterprise environments

• Ability to work effectively across cross‑functional teams and global time zones, with strong communication skills and the ability to influence both technical and non‑technical stakeholders

• Proven ability to drive technical decisions, mentor peers, and contribute to a high‑performing engineering culture

How You will find success

• Cultivate a strong sense of curiosity and a product-focused mindset

• Collaborate effectively with managers, cross-functional teams, and teammates to achieve shared goals

• Demonstrate persistence, creativity, and an unwavering drive to deliver results

• Take pride in ownership and consistently strive for excellence in every initiative

• Apply an analytical approach to tackle complex problems, identify root causes, and develop data-driven, impactful solutions

Equinix is committed to ensuring that our employment process is open to all individuals, including those with a disability.  If you are a qualified candidate and need assistance or an accommodation, please let us know by completing this form.

Equinix is an Equal Employment Opportunity and, in the U.S., an Affirmative Action employer.  All qualified applicants will receive consideration for employment without regard to unlawful consideration of race, color, religion, creed, national or ethnic origin, ancestry, place of birth, citizenship, sex, pregnancy / childbirth or related medical conditions, sexual orientation, gender identity or expression, marital or domestic partnership status, age, veteran or military status, physical or mental disability, medical condition, genetic information, political / organizational affiliation, status as a victim or family member of a victim of crime or abuse, or any other status protected by applicable law. 

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