Software Engineer

Software Engineer

Location: Remote

Description:
As a Tech Lead Software Engineer, you are a hands on technical leader with end to end ownership of service level architecture, delivery outcomes, and production reliability. You set technical direction, make and communicate clear architectural tradeoffs, and lead through influence—aligning engineers, product, and partners around durable, scalable solutions.

You design, build, and operate backend services as the organization modernizes from on prem to AWS, applying cloud native and event driven patterns to improve reliability, security, and developer velocity. You champion build it / run it ownership, ensuring services meet clear standards for quality, observability, and operational excellence.

You accelerate delivery through AI  and agentic first engineering practices, establishing safe, repeatable workflows that improve throughput and quality while maintaining strong validation, security, and governance. You raise the engineering bar by mentoring others, setting clear guardrails, and continuously improving the systems and practices your teams rely on.

Technical Leadership:

• Set and communicate technical direction, aligning engineers around clear priorities, architectural intent, and delivery outcomes 
• Lead through influence, partnering with product, platform, and dependent teams to drive alignment without relying on positional authority 
• Serve as the primary technical escalation point, resolving complex challenges while balancing speed, quality, and long term sustainability 
• Raise the engineering bar, mentoring through design reviews, code reviews, and shared standards that elevate team capability 
• Model ownership and accountability, leading by example with a bias for action and end to end responsibility

Modern Software Development:

• Own service level architecture and technical decisions, defining APIs, data models, messaging patterns, resiliency, and error handling that scale and endure 
• Lead system modernization, decomposing monoliths into well bounded, cloud native services using domain driven and evolutionary architecture principles 
• Design and evolve event driven systems, establishing reliable pub/sub patterns, schema and versioning strategies, and failure handling 
• Set data architecture direction, modeling access patterns across relational and NoSQL stores for correctness, performance, and cost efficiency 
• Establish architectural guardrails, using patterns, reference implementations, and lightweight reviews to enable autonomy with alignment 
• Make and revisit pragmatic tradeoffs, documenting decisions and adapting as requirements, scale, or constraints change

Agentic AI–First Engineering:

• Lead adoption of AI  and agentic first development practices, integrating AI into coding, testing, reviews, documentation, and CI/CD 
• Design governed, repeatable agentic workflows for multi step engineering tasks, with clear human in the loop controls 
• Set standards for validating AI outputs, ensuring security, correctness, maintainability, and standards alignment 
• Measure and optimize impact, improving throughput, quality, and developer experience based on outcomes—not novelty 
• Enable responsible experimentation, empowering teams to innovate within defined guardrails and shared learnings

Quality, Delivery & Operations:

• Own production quality and reliability, ensuring services meet clear expectations for availability, performance, and resiliency
• Define and enforce quality mechanisms, establishing testing strategies, CI quality gates, and review standards that make correctness the default
• Operate what you build, taking end to end responsibility from development through deployment, on call readiness, and incident remediation
• Lead operational excellence, defining observability standards, SLIs/SLOs, and actionable alerts to proactively manage system health
• Ensure predictable delivery, improving flow through automation, CI/CD maturity, and reduced operational friction
• Embed security and compliance by design, addressing regulatory and risk requirements without slowing delivery
• Drive continuous improvement, using incidents, metrics, and retrospectives to strengthen systems, processes, and practices

Education & Experience Requirements
Must-Have

• 8–10+ years of professional software engineering experience, with sustained ownership of backend systems in production 
• Demonstrated technical leadership as a Tech Lead or senior IC—owning service level architecture, influencing decisions, and serving as a technical escalation point 
• Strong backend engineering experience designing and operating secure, scalable services (Java or JVM based environments preferred) 
• Production experience building cloud based systems, including hands on experience with AWS (compute, messaging, storage) and cloud native patterns 
• Experience designing event driven architectures, including publish/subscribe patterns, message durability, idempotency, retries, and failure handling 
• Build it / run it ownership mindset, with experience supporting services in production, participating in on call, and driving incident remediation 
• Strong quality discipline, including test strategy (unit, integration, contract), CI/CD quality gates, and rigorous code review practices 
• Proven ability to collaborate across teams, working effectively with product, platform, security, and dependent engineering groups 
• Excellent technical communication skills, able to clearly document and explain architectural decisions and tradeoffs

Nice-to-Have

• Experience modernizing legacy or on prem systems, including decomposition strategies and evolutionary migration to AWS 
• Practical application of domain driven design concepts, such as bounded contexts, aggregates, and hexagonal architectures 
• Experience with AI assisted or agentic development tools, and familiarity with defining guardrails and validation practices 
• Experience with containerization, orchestration, or serverless platforms, such as Docker, Kubernetes/EKS, ECS, or Lambda 
• Infrastructure as Code experience, using tools like Terraform or CDK 
• Experience with observability platforms (e.g., New Relic, Datadog, Prometheus) and SLO driven reliability practices 
• Experience with NoSQL data stores, such as MongoDB or Redis, and performance aware data modeling 
• Familiarity with API gateways and integration patterns, such as Kong or Apigee 
• Experience operating in regulated environments, with awareness of PCI, SOX, or similar requirements