RESPONSIBILITIES
- Experience building agentic harnesses from scratch, including capabilities such as tool use, multi-step chaining, reasoning, streaming, skills, multimodal integration, RAG, sandboxing, and state management.
- Experience designing, building, and operating production APIs and services, including RESTful APIs, streaming APIs, asynchronous workflows, service boundaries, versioning, authentication/authorization, error handling, and backward compatibility. Strong judgment around when to use synchronous APIs, event-driven architectures, queues, background jobs, or streaming protocols based on latency, reliability, scalability, and user experience requirements.
- Demonstrated ownership of production systems, including process improvements, roadmap contributions, defect resolution, uptime and availability monitoring, and operational reliability.
- Strong backend engineering fundamentals, with comfort working across service design, APIs, batch workflows, orchestration, observability, and production support.
- Familiarity with evaluation techniques such as creating and maintaining evaluation datasets, running offline regression evals, monitoring online production performance, rubric-based scoring, self-verification, human-in-the-loop review, AI-as-judge methods, and quality/reliability analysis at scale.
- Clear understanding of foundational machine learning and statistical concepts, including sampling, statistical significance, overfitting/underfitting, precision and recall, and quality tradeoff analysis.
- Experience building and orchestrating large-scale batch workflows that use foundation models, including LLMs and VLMs, as well as pretrained open-source models and deep learning models.
- Ability to design systems that safely and reliably automate meaningful enterprise workflows using non-deterministic AI components.
- Strong judgment around reliability, failure handling, observability, human review, and operational safety.
- Deep understanding of how to make systematic tradeoffs between quality, reliability, latency, cost, explainability, and user experience in complex AI systems.
- Ability to design pragmatic architectures that balance innovation with production readiness.
- Comfort working in environments where model behavior is non-deterministic and system design must account for uncertainty, evaluation, monitoring, and graceful failure.
- Experience with both lexical and embedding-based search methods.
- Ability to reason about relevance, ranking, latency, recall, precision, indexing strategy, and retrieval performance.
- Experience working with foundation models and open-source LLMs beyond simple API calls.
- Familiarity with lower-level model behaviors and controls, including temperature, top-p sampling, logprobs, confidence scoring, prompting strategies, and model selection tradeoffs.
- Comfort and willingness to build front-end experiences using JavaScript/TypeScript and frameworks such as React.
- While the role is primarily backend and AI systems focused, the ability to contribute to user-facing product experiences is important.
- Willingness to work across the stack and own the end-to-end product experience is essential.
Familiarity with tools such as FFmpeg, OpenCV, or similar media-processing libraries is a plus.
QualificationsQUALIFICATIONS/REQUIREMENTS
- 7+ years of a programming languages such as Java, Golang, Python, JavaScript
- 2+ years of experience architecting, designing, and optimizing search and information retrieval systems at scale.
- 6 months to 1 year of hands-on experience building agentic products or solutions, including tool-using agents, conversational agents, long-running agents, reasoning/planning agents, or similar systems.
- Experience with multiple modern agent frameworks is preferred. Specific frameworks are less important than demonstrated fluency, but exposure to tools such as OpenAI Agents SDK, LangGraph, Google ADK, SmolAgents, or comparable frameworks is valuable.
- 1+ year of experience evaluating AI systems for quality, reliability, and safety at scale.
- 5+ years of experience shipping production software in an enterprise or consumer environment, not just prototypes or proofs of concept.
- OpenSearch or Elasticsearch experience is preferred, but comparable experience with other search and retrieval systems is sufficient.
- Expert experience, understanding and knowledge of digital and broadcast production operations and workflows
- Experience working with video, rich visual media, or multimodal AI systems.
- Strong knowledge of industry trends and best practices
- Strong experience with the C4 model and other traditional design artifacts
- Experience working in an Agile environment
DESIRED CHARACTERISTICS
- Experience with training, fine-tuning, or adapting models for domain-specific use cases using techniques such as LoRA, PEFT, or related approaches.
- Exposure to stateful software design patterns and streaming protocols such as WebSockets
- Familiarity with client-side web technologies (React, Angular, JavaScript, CSS, HTML)
- 5+ years working with the AWS cloud
- 1+ years working with the Azure cloud
- Familiarity with continuous integration/delivery practices
- Docker, Kubernetes experience a plus
- BS in CS, EE or equivalent experience required
All your information will be kept confidential according to EEO guidelines.
EEOC and Veteran Documentation
During employment, employees are treated without regard to race, color, religion, sex, national origin, age, marital or veteran status, medical condition or handicap, or any other legally protected status.
At times, government agencies require periodic reports from employers on the sex, ethnicity, handicap, veteran and other protected status of employees. The purpose of this Administrative EEO Record is for statistical analysis only and is used to comply with government record keeping, reporting, and other legal requirements. Periodic reports are made to the government on the following information. The completion of the Administrative EEO record is optional. If you choose to volunteer the requested information, please note that all
Administrative EEO Records are kept in a Confidential File and are not part of your Application for Employment or Personnel file.
Please note: YOUR COOPERATION IS VOLUNTARY. INCLUSION OR EXCLUSION OF ANY DATA WILL NOT AFFECT ANY EMPLOYMENT DECISION.
Skills Required
- 7+ years programming experience in Java, Golang, Python, or JavaScript
- 2+ years architecting, designing, and optimizing search and information retrieval systems at scale
- 6 months to 1 year hands-on experience building agentic products (tool-using, conversational, planning or long-running agents)
- 1+ year evaluating AI systems for quality, reliability, and safety at scale
- 5+ years shipping production software in enterprise or consumer environments
- Expert knowledge of digital and broadcast production operations and workflows
- Experience working with video, rich visual media, or multimodal AI systems
- Strong backend engineering fundamentals: service design, APIs, batch workflows, orchestration, observability, production support
- Familiarity with evaluation techniques: datasets, offline regressions, online monitoring, rubric scoring, human-in-the-loop
- Experience building and operating production APIs and services (versioning, auth, error handling, async workflows, streaming)
- Strong experience with the C4 model and traditional architecture design artifacts
- BS in Computer Science, Electrical Engineering, or equivalent experience
- Experience with multiple modern agent frameworks (exposure to OpenAI Agents SDK, LangGraph, Google ADK, SmolAgents preferred)
- OpenSearch or Elasticsearch experience (preferred, comparable search experience acceptable)
- Experience with training, fine-tuning, or adapting models using LoRA, PEFT, or similar approaches
- Exposure to stateful software design patterns and streaming protocols (e.g., WebSockets)
- Comfort building front-end experiences using JavaScript/TypeScript and frameworks such as React
- 5+ years working with AWS
- 1+ years working with Azure
- Familiarity with continuous integration/delivery practices
- Docker and Kubernetes experience
- Familiarity with media-processing libraries (FFmpeg, OpenCV) is a plus
- Ability to design systems that safely automate enterprise workflows using non-deterministic AI components
Sutherland Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Sutherland and has not been reviewed or approved by Sutherland.
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Flexible Benefits — Flexible scheduling and work-from-home arrangements are offered on certain programs, supported by remote-work infrastructure and virtual IT support. Program-specific flexibility is emphasized for “Sutherland Anywhere” roles.
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Leave & Time Off Breadth — Paid time off and paid training are positioned as standard elements, with some materials also highlighting flexible vacation days. Core leave features are presented as part of the baseline package.
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Strong & Reliable Incentives — Performance incentives, bonuses, and commissions are available on selected programs to supplement base pay. Goal-linked earnings opportunities are described for certain functions.
Sutherland Insights
What We Do
We make digital ?????™ by combining human-centered design with real-time Analytics, AI, Cognitive Technology & Automation to create exceptionally engineered Brand Experiences! Sutherland is an experience-led digital transformation company. Our mission is to deliver exceptionally engineered experiences for customers and employees today, that continue to delight tomorrow. For over 35 years, we have cared for our customers’ customers, delivering measurable results and accelerating growth. Our proprietary, AI-based products and platforms are built using robust IP and automation. We are a team of global professionals, operationally effective, culturally meshed, and committed to our clients and to one another. We call it One Sutherland. #MakeDigitalHuman








