DevSavant is an operating partner for startups and growth-stage companies, helping them turn ambition into execution.
We support founders and leadership teams with product engineering and global staffing, from early prototypes and MVPs to scaling high-performing teams. Our vetted talent across LATAM and Asia embeds directly into client teams, operating as true extensions rather than external vendors.
With over 8 years working in venture-backed ecosystems, DevSavant is trusted to accelerate delivery, scale teams efficiently, and support companies as they reach their next milestone.
We are seeking Senior Backend Software Engineers to join our distributed engineering team.
This is an individual contributor role embedded within cross-functional teams, focused on building and maintaining the backend services and infrastructure that power our AI platform. The role is heavily backend-oriented, with a strong emphasis on designing and developing scalable, reliable services using Python in an AWS environment.
While familiarity with AI systems and production LLM patterns is a strong plus, the core need is for engineers who can build robust APIs, data pipelines, integrations, and infrastructure that enable our AI-driven products to operate effectively at scale.
The ideal candidate is a hands-on engineer who thrives in fast-paced environments, takes ownership, and is comfortable working with evolving requirements.
Build and maintain backend services using Python and FastAPI within a microservices architecture
Design and implement scalable, reliable APIs and data processing systems
Contribute to both new platform development and legacy systems as needed
Write clean, well-tested, and maintainable code following best practices
Participate actively in code reviews and continuous improvement of engineering standards
Own integrations with third-party systems such as CRMs, DMS platforms, inventory systems, and communication tools
Build and maintain data ingestion and synchronization pipelines across multiple data sources
Support email, SMS, and chat delivery infrastructure
Ensure data consistency, reliability, and performance across services
Work within an AWS-based infrastructure (EKS/Kubernetes and related services)
Contribute to highly reliable and observable systems through logging, metrics, and alerting
Collaborate on CI/CD pipelines using GitLab
Utilize observability tools such as Datadog to monitor system health and performance
Collaborate closely with product managers, engineering leads, and cross-functional teams
Translate evolving and sometimes ambiguous requirements into working software solutions
Take ownership of features and systems, driving them from concept to production
Operate effectively in a distributed, remote-first environment across time zones
Python as the primary language (PHP + Python in legacy systems)
FastAPI for new services (with some legacy Django components)
PostgreSQL as the main database (MySQL in legacy systems)
Microservices architecture deployed on Kubernetes (EKS) on AWS
AWS-centric infrastructure (EKS, S3, SQS, Lambda, etc.)
GitLab for CI/CD pipelines
Datadog for logging, monitoring, and observability
5+ years of professional backend software engineering experience
Strong proficiency in Python with experience building production-grade services
Experience with web frameworks such as FastAPI, Django, or Flask
Solid understanding of relational databases (PostgreSQL and/or MySQL), including schema design, query optimization, and migrations
Experience with cloud infrastructure, preferably AWS (EC2, ECS/EKS, S3, SQS, Lambda, or similar)
Familiarity with containerization and orchestration (Docker, Kubernetes)
Experience building and maintaining RESTful APIs and data integration pipelines
Strong foundation in software engineering practices: Git, testing, CI/CD, and code reviews
Strong communication skills and ability to collaborate in distributed teams across time zones
Proactive, curious mindset with a focus on continuous improvement
Active use of AI coding tools (e.g., GitHub Copilot, Claude Code, Cursor) in daily workflows
Working proficiency in English for team communication and documentation
Familiarity with agentic AI patterns and production LLM systems
Experience with production AI systems (RAG pipelines, LLM integrations, agent orchestration)
Experience managing AWS infrastructure using Terraform
Familiarity with observability tools such as Datadog
Experience working with data from CRMs, DMS platforms, or marketing automation systems
Experience in B2B SaaS environments
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