Engenheiro de Software Sénior

Job Description

Titan Advanced Energy Solutions, headquartered in Salem, MA, develops revolutionary, ultrasound-based battery cell inspection systems for gigafactories. Using non-destructive, high-resolution, high-speed ultrasound technology, Titan's IonSight analyses cell morphology to detect critical manufacturing anomalies, directly addressing safety concerns and improving processes.

Located in Salem, MA, Titan's innovative strides have been recognized with numerous awards and funding from multi-national corporate investment groups, venture capital and top clean energy programs and institutions, including Greentown Labs, the Massachusetts Clean Energy Center (MassCEC) and the Department of Energy. Growing and poised to continue their positive momentum, this is an exciting time to join the Titan team!

We are looking for a Senior Software Engineer to join our innovative and dynamic team. Our mission is to propel the shift toward world electrification and decarbonization by scaling battery manufacturing technology more efficiently.

Summary

The Sr. Software Engineer will own end-to-end delivery across AWS infrastructure, CI/CD, backend services, and a TypeScript/React web application. You will also shape how that software runs in two very different places: in the cloud, and on-prem at the edge on a customer's factory floor, from the same codebase. A scan takes about a second and produces hundreds of thousands of data points, so how that data moves, queues, and gets processed is an architectural problem as much as an application one. You'll build new product areas and improve reliability, security, and developer velocity.

What you'll do

• Design, implement, and operate AWS infrastructure using IaC (we use Terragrunt/Terraform): VPC/networking, IAM, ECS/Fargate, ALB, WAF, RDS/Aurora Postgres, S3, CloudWatch, Route53/ACM, and application auth (we use Clerk).
• Architect for dual deployment: the same product delivered as a cloud service and as an on-prem/edge install, with the packaging, configuration, update, and observability story that makes both dependable.
• Design the path data takes from the scanner to the customer: messaging and event-driven patterns (we use RabbitMQ), queuing, backpressure, and asynchronous processing of high-volume scan data.
• Model, store, and serve the time-series data coming off live scans: continuous ingest, retention and down-sampling, streaming results to the application in real time, and query performance that holds as sites and history accumulate.
• Own CI/CD in GitHub Actions: build/test pipelines, container build/publish, environment deployments, on-prem release artifacts, and release/versioning automation.
• Build backend APIs in Python (FastAPI): async patterns, Postgres data modeling, migrations, and production-grade observability and error handling.
• Build frontend features in React/TypeScript with server-side rendering: routing, data loading and mutations, component patterns, and secure integrations with backend and AWS services.
• Apply AI and LLM capabilities where they earn their place, both in the product and in how we build: retrieval over inspection data, natural-language access to results, and agentic tooling for internal workflows.
• Lead architecture and execution: break down ambiguous work, drive cross-cutting improvements (performance/security/cost), review code, and mentor engineers.
• Partner with the Machine Learning team, who own the models and ML pipelines, and provide the platform, edge runtime, transport, and application those models run on.

Required skills

• Strong AWS experience in production and comfort operating distributed systems.
• Infrastructure-as-code experience, such as Terragrunt/Terraform.
• Ownership of the architecture of a non-trivial distributed system: the trade-offs, the failure modes, and how the design evolved as load and deployments grew.
• Messaging and event-driven systems with asynchronous processing at volume, such as RabbitMQ: exchanges and queues, worker patterns, idempotency, retries and dead-lettering, and backpressure.
• Strong TypeScript and React experience; server-side rendering experience, such as Next.js, preferred.
• Experience with time-series data and live streaming: a purpose-built time-series store, real-time delivery to clients (WebSockets or SSE), and handling sustained high-rate ingest.
• Strong Python backend experience (FastAPI or similar) with relational databases (Postgres) and migrations.
• Docker/container workflows, CI/CD ownership, and secure auth fundamentals (JWT/OIDC, RBAC/scopes).
• Practical experience building on AI/LLM APIs, with a clear sense of where they help and where they do not.

Nice to have

• Edge or on-prem delivery: shipping software onto hardware you do not control, with constrained networking, offline operation, and remote update.
• Deep AWS security/operations: WAF hardening, least-privilege IAM, secrets management, audit readiness.
• Multi-environment and multi-tenant deployment experience.
• Experience integrating managed ML/inference services (e.g., SageMaker/Triton) and handling data-heavy workflows.
• Industrial, manufacturing, or IoT settings where software meets physical equipment.
• Startup experience, and comfort in a small team where scope is broad and priorities move.

Personal Values

• Bias to action, self-motivated and entrepreneurial spirit
• Attention to detail, effective time management, and pride in work
• Dependable, trustworthy, empathetic & full of integrity
• Strong collaborative communication skills; able to build consensus internally and externally

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Engineering and Information Technology

Industries

Climate Technology Product Manufacturing