Smarsh Visa Sponsorship Jobs USA
Smarsh is a compliance technology company specializing in digital communications archiving and surveillance for regulated industries. It has an active sponsorship track record across H-1B visa, Green Card, F-1 OPT, and TN visa types, making it a credible option for international candidates in software engineering and compliance technology roles.
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Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.
Smarsh is hiring a senior backend/platform engineer to build and scale agentic AI systems for enterprise use. You will build fast-moving, early-stage Python services that integrate AI capabilities into a production agentic platform. Your scope spans workflow execution, scale, reliability, and platform hardening as we grow.
This is not a generic backend role. The focus is building and designing agentic systems, shipping working software, and solving hard platform problems in a fast-moving AI-native environment. You will join a small, high-velocity cross-functional group and own problems end to end, designing and building from scratch, making fast architectural calls, and driving ideas from whiteboard to working system with a small, high-agency team.
What will you do?
- Drive backend development for AI workflows as part of a collaborative team. Build and evolve Python/FastAPI services powering core agentic workflows and platform capabilities.
- Productionize LLM integrations. Implement systems around Bedrock usage, quotas, retries, failover, cost controls, model configuration, and approval constraints.
- Design for security and compliance. Address customer data handling, tenant isolation, auditability, observability, and secure processing for regulated workloads. Apply auditable data design patterns to ensure AI outputs are traceable, reproducible, and built to withstand regulatory scrutiny.
- Build for scale. We're a nimble team, but our enterprise customers process data at petabyte scale. Help the platform grow to meet that bar through async job orchestration, performance tuning, and data-layer optimization.
- Support multi-tenant architecture. Contribute to tenant-aware services, role-based access, SSO integration, and admin/reporting capabilities.
- Improve platform reliability. Add monitoring, tracing, alerting, and operational tooling for LLM pipelines, workflow execution, and report generation.
- Build real-time capabilities. Design and implement real-time event delivery and pub/sub patterns to support live workflow state, notifications, and agent feedback loops.
- Contribute to technical decisions. Partner on shared services decisions, platform architecture, and integration boundaries across the stack.
- Work across ambiguity. Translate evolving product requirements and non-functional requirements into practical technical solutions with product, architecture, legal, and security stakeholders.
- Champion code quality. Drive strong typing, automated testing, and continuous integration practices that keep the team fast and safe.
- Design typed API contracts. Own the API surface as a product contract: designing clean, schema-driven APIs that support typed client generation and reliable integration across services.
What will you bring?
- Strong Python backend engineering. 7+ years professional software development, including 5+ years building Python services in production. Deep experience with APIs, async processing, background jobs, and workflow orchestration.
- Cloud-native backend experience. AWS experience, ideally with services relevant to secure enterprise workloads (compute, storage, networking, CI/CD, identity, secrets, encryption).
- Production distributed systems. Proven ability to productionize complex backend systems with reliability, observability, retries, throughput, failure handling, and performance tuning.
- Data-intensive system design. Strong knowledge of PostgreSQL, large-scale data processing patterns, indexing, query tuning, and batch/stream tradeoffs. Experience with retrieval-augmented generation (RAG), vector search, and embedding-based systems is required (not a plus).
- Security and compliance mindset. Experience with multi-tenant systems, RBAC, audit logging, secure data handling, and regulated environments.
- Strong ambiguity handling. Ability to work from partial requirements and shape implementation around product and non-functional requirement constraints.
- Agentic workflow engineering. Hands-on experience building LLM-driven workflows: tool-calling, state machines, human-in-the-loop approval patterns, checkpoint/resume, and multi-step agent orchestration. Familiarity with frameworks like LangGraph or equivalent.
- AI-native engineering. Experience working on or alongside AI-native engineering teams, where AI agents are first-class participants in the development workflow, not just productivity tools. Includes hands-on prompt engineering, eval design, and LLM cost optimization: caching strategies, token efficiency, and model selection tradeoffs.
- Product mindset. Bias for shipping, learning from real usage, and making pragmatic tradeoffs grounded in customer problems.
Strong Pluses
- LLM / AI platform experience. Bedrock, OpenAI, Anthropic, LangChain/LangGraph, prompt workflows, evals, tool-calling systems. Experience integrating external AI services safely and reliably.
- Identity and access. SSO/SAML/OIDC, enterprise auth patterns.
- Graph-shaped data and entity resolution. Experience with graph-backed data models, entity deduplication, mention linking, and building systems that reason over connected, structured records.
- Observability stack. OpenTelemetry, tracing, metrics, alerting, cost/usage dashboards.
- Regulated communications or compliance domain. Background in systems that handle sensitive communications, audit trails, or data subject to legal or regulatory review is a meaningful differentiator.
- Infrastructure as code. Terraform, feature flags, canary deployments, release strategies.
The salary range above represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting. Any applicable bonus programs will be discussed during the recruiting process.
The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training.
Local cost of living assessments are done for each new hire at the time of offer.
About our culture
Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world’s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.
Who are we?
Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.
Smarsh is hiring a senior backend/platform engineer to build and scale agentic AI systems for enterprise use. You will build fast-moving, early-stage Python services that integrate AI capabilities into a production agentic platform. Your scope spans workflow execution, scale, reliability, and platform hardening as we grow.
This is not a generic backend role. The focus is building and designing agentic systems, shipping working software, and solving hard platform problems in a fast-moving AI-native environment. You will join a small, high-velocity cross-functional group and own problems end to end, designing and building from scratch, making fast architectural calls, and driving ideas from whiteboard to working system with a small, high-agency team.
What will you do?
- Drive backend development for AI workflows as part of a collaborative team. Build and evolve Python/FastAPI services powering core agentic workflows and platform capabilities.
- Productionize LLM integrations. Implement systems around Bedrock usage, quotas, retries, failover, cost controls, model configuration, and approval constraints.
- Design for security and compliance. Address customer data handling, tenant isolation, auditability, observability, and secure processing for regulated workloads. Apply auditable data design patterns to ensure AI outputs are traceable, reproducible, and built to withstand regulatory scrutiny.
- Build for scale. We're a nimble team, but our enterprise customers process data at petabyte scale. Help the platform grow to meet that bar through async job orchestration, performance tuning, and data-layer optimization.
- Support multi-tenant architecture. Contribute to tenant-aware services, role-based access, SSO integration, and admin/reporting capabilities.
- Improve platform reliability. Add monitoring, tracing, alerting, and operational tooling for LLM pipelines, workflow execution, and report generation.
- Build real-time capabilities. Design and implement real-time event delivery and pub/sub patterns to support live workflow state, notifications, and agent feedback loops.
- Contribute to technical decisions. Partner on shared services decisions, platform architecture, and integration boundaries across the stack.
- Work across ambiguity. Translate evolving product requirements and non-functional requirements into practical technical solutions with product, architecture, legal, and security stakeholders.
- Champion code quality. Drive strong typing, automated testing, and continuous integration practices that keep the team fast and safe.
- Design typed API contracts. Own the API surface as a product contract: designing clean, schema-driven APIs that support typed client generation and reliable integration across services.
What will you bring?
- Strong Python backend engineering. 7+ years professional software development, including 5+ years building Python services in production. Deep experience with APIs, async processing, background jobs, and workflow orchestration.
- Cloud-native backend experience. AWS experience, ideally with services relevant to secure enterprise workloads (compute, storage, networking, CI/CD, identity, secrets, encryption).
- Production distributed systems. Proven ability to productionize complex backend systems with reliability, observability, retries, throughput, failure handling, and performance tuning.
- Data-intensive system design. Strong knowledge of PostgreSQL, large-scale data processing patterns, indexing, query tuning, and batch/stream tradeoffs. Experience with retrieval-augmented generation (RAG), vector search, and embedding-based systems is required (not a plus).
- Security and compliance mindset. Experience with multi-tenant systems, RBAC, audit logging, secure data handling, and regulated environments.
- Strong ambiguity handling. Ability to work from partial requirements and shape implementation around product and non-functional requirement constraints.
- Agentic workflow engineering. Hands-on experience building LLM-driven workflows: tool-calling, state machines, human-in-the-loop approval patterns, checkpoint/resume, and multi-step agent orchestration. Familiarity with frameworks like LangGraph or equivalent.
- AI-native engineering. Experience working on or alongside AI-native engineering teams, where AI agents are first-class participants in the development workflow, not just productivity tools. Includes hands-on prompt engineering, eval design, and LLM cost optimization: caching strategies, token efficiency, and model selection tradeoffs.
- Product mindset. Bias for shipping, learning from real usage, and making pragmatic tradeoffs grounded in customer problems.
Strong Pluses
- LLM / AI platform experience. Bedrock, OpenAI, Anthropic, LangChain/LangGraph, prompt workflows, evals, tool-calling systems. Experience integrating external AI services safely and reliably.
- Identity and access. SSO/SAML/OIDC, enterprise auth patterns.
- Graph-shaped data and entity resolution. Experience with graph-backed data models, entity deduplication, mention linking, and building systems that reason over connected, structured records.
- Observability stack. OpenTelemetry, tracing, metrics, alerting, cost/usage dashboards.
- Regulated communications or compliance domain. Background in systems that handle sensitive communications, audit trails, or data subject to legal or regulatory review is a meaningful differentiator.
- Infrastructure as code. Terraform, feature flags, canary deployments, release strategies.
The salary range above represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting. Any applicable bonus programs will be discussed during the recruiting process.
The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training.
Local cost of living assessments are done for each new hire at the time of offer.
About our culture
Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world’s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.
Job Roles at Smarsh
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Get Access To All JobsTips for Finding Smarsh Visa Sponsorship Jobs USA
Target roles in compliance and archiving technology
Smarsh's core product suite centers on communications compliance for financial services firms. Engineering, data, and platform roles tied to this stack are where sponsorship activity is most concentrated, prioritize these when searching.
Understand Smarsh's regulated-industry focus
Smarsh serves heavily regulated clients in finance and banking. Candidates who can speak to compliance workflows, data retention requirements, or financial communications infrastructure will stand out in interviews and applications.
Check for F-1 OPT roles if you're on a student visa
Smarsh has sponsored F-1 OPT candidates alongside H-1B holders. If you're currently on OPT, this matters, look for roles that align with your degree field to support a smooth OPT-to-H-1B transition with the same employer.
Use Migrate Mate to filter by verified sponsorship history
Not every job posting flags visa sponsorship clearly. Migrate Mate surfaces verified sponsors so you can filter by real sponsorship history and find open roles at Smarsh without sifting through listings that don't support international candidates.
Explore TN visa eligibility if you're Canadian or Mexican
Smarsh sponsors TN visas in addition to H-1B, which is a faster and cap-exempt pathway for qualifying Canadian and Mexican nationals. If you hold a TN-eligible occupation like software engineer or engineer, this route is worth exploring.
Prepare for a technical and compliance-aware interview process
Smarsh interviews tend to probe both technical depth and understanding of enterprise software in regulated environments. Demonstrating familiarity with compliance, security, or SaaS infrastructure will strengthen your candidacy alongside standard engineering assessments.
Frequently Asked Questions
Does Smarsh sponsor H-1B visas?
Yes, Smarsh sponsors H-1B visas. The company has a consistent track record of H-1B filings, primarily for technical roles in software engineering, platform development, and data infrastructure. If you're targeting Smarsh on an H-1B, focus your application on roles that align directly with their compliance technology product suite.
Which visa types does Smarsh sponsor?
Smarsh sponsors H-1B, Green Card (EB-2 and EB-3), F-1 OPT, and TN visas. Green Card sponsorship indicates a willingness to support long-term immigration pathways, not just temporary work authorization. TN sponsorship is particularly relevant for qualified Canadian and Mexican nationals in technical occupations.
Which departments or roles at Smarsh are most likely to receive visa sponsorship?
Sponsorship at Smarsh is concentrated in technical and engineering functions, reflecting the company's identity as a compliance software provider. Roles in software development, cloud infrastructure, data engineering, and platform architecture are the most common sponsored positions. Product and technical program management roles may also qualify depending on the specific job requirements.
How do I find open visa-sponsored jobs at Smarsh?
Migrate Mate is the most efficient way to browse open roles at Smarsh with confirmed sponsorship history. Rather than filtering through general job listings that rarely specify visa support, Migrate Mate lets you search by company and visa type so you can quickly identify which Smarsh openings align with your immigration status and qualifications.
How do I time my application to Smarsh around the H-1B cap?
H-1B cap-subject petitions must be filed by April 1 for an October 1 start date, which means employers need to submit registrations in March. To work backward, you should have an offer and completed documentation by late February at the latest. Starting your application to Smarsh in the fall or winter before the lottery gives you the most runway.