Senior Staff Software Engineer

Overview Why we are looking for you:

• You have a passion for AI and platform engineering.
• You have a deep understanding of AI, not just applied conversational AI but the mechanics of a working AI system in production.
• You can operate as a senior technical authority who connects enterprise AI strategy, platform architecture, governance, and delivery execution.
• You are comfortable solving ambiguous, cross-business-unit problems where reusable AI platforms, assets, and standards must scale beyond a single use case.
• You have successfully delivered AI agents with measurable business benefit.

What You Will Enjoy In This Role

• A senior individual contributor role with high visibility across product, engineering, data, security, finance, and business partners.
• Exposure to a range of top-notch enterprise scale AI solutions
• Access to a global user base and all Epsilon internal and external solutions
• Ownership for building platforms and solutions of strategic importance for Epsilon.
• Working with top AI talent that has delivered applied AI solutions at scale.
• Opportunity to shape enterprise-wide AI architecture patterns, reusable accelerators, governance controls, and platform standards adopted across teams.

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Responsibilities

• Understand end-user requirements and expectations from AI solutions; translate to effective architecture and design.
• Deliver platforms that enable effective and secure use of AI, specifically through improved Cost management, Governance and Discoverability.
• Build interoperability across hyper-scalers and agent development tools to standardize AI spend management and governance.
• Lead architecture and technical design for reusable AI platforms, agent frameworks, RAG pipelines, evaluators, orchestration services, APIs, and integrations with enterprise systems.
• Define reference architectures, engineering standards, guardrails, and delivery patterns that improve reliability, observability, security, scalability, and cost efficiency of AI solutions.
• Guide build-versus-buy decisions, model and platform selection, and architectural trade-offs across foundation models, cloud AI services, open-source frameworks, and enterprise tooling.
• Establish evaluation, testing, monitoring, feedback-loop, and runbook practices for production AI systems, including hallucination risk, quality benchmarks, latency, token usage, and operational health.
• Partner with business units to assess AI opportunities, validate feasibility, define measurable success criteria, and convert promising use cases into scalable platform capabilities.
• Mentor engineers and influence technical execution across teams through design reviews, code quality standards, reusable components, documentation, and hands-on engineering guidance.
• Work closely with AI engineers in team to ensure high quality, reliable solutions and platforms.

Qualifications

• 12-18 years of experience building enterprise scale web applications.
• Grounded, hands-on experience building Generative AI solutions, ML solutions, MLOps pipeline, and building agentic AI workflows, preferably in Microsoft tech stack.
• Strong hands-on engineering depth in Python and modern backend architectures, with the ability to design scalable APIs, services, integrations, and reusable libraries for AI applications.
• Deep understanding of LLM application patterns including RAG, prompt orchestration, tool/function calling, structured outputs, agentic workflows, multi-agent orchestration, and human-in-the-loop controls.
• Experience with AI platform capabilities such as vector databases, feature stores, model serving, evaluation frameworks, observability, tracing, usage metering, and cost optimization.
• Working knowledge of cloud AI and data platforms such as AWS Bedrock, Azure OpenAI, Azure AI Foundry, Databricks, containerized services, serverless patterns, and cloud-native deployment approaches.
• Ability to embed responsible AI practices including security, privacy, RBAC, model governance, auditability, compliance controls, restricted-topic handling, and production-readiness reviews.
• Proven ability to influence senior engineers, architects, product leaders, and business stakeholders through clear technical communication, decision frameworks, and outcome-driven architecture leadership.

Additional Information Epsilon is a global data, techno…