Principal Software Engineer na Invisible Technologies

Híbrido - New York

Invisible Technologies is seeking a Principal Software Engineer to join its AI/ML team. The role involves full-stack development, backend technologies, and Agentic AI. Responsibilities include building scalable backend systems, supporting client‑facing deployments, optimizing cloud infrastructure, collaborating with ML engineers and data scientists, and engaging directly with clients for use case discovery. The position requires 5+ years of software engineering experience with a focus on ML engineering, strong proficiency in Python, experience with LLMs, AI Agents, RAG pipelines, cloud platforms (AWS, GCP, Azure), Kubernetes, unit and E2E testing, polyglot persistence models, MLOps frameworks, and DevOps practices. Compensation ranges from $243,000 to $286,000 annually for Tier 1 locations. The company values fairness, competitive pay, bonuses, equity, and offers a hybrid work arrangement in New York.

Salary

USD 243,000 - 286,000/year

Requirements

Experience

5+ years of software engineering experience, with a strong focus on ML engineering and deploying machine learning models in production.

Skills

Python
LLMs
AI Agents
ML model development
scalable ML systems
retrieval‑augmented generation (RAG) pipelines
production‑grade AI applications
cloud platforms (AWS, GCP, Azure)
Kubernetes
container management
unit tests
E2E tests
polyglot persistence models (SQL vs NoSQL)
MLOps frameworks
DevOps principles
model versioning
monitoring
lifecycle management

Responsibilities

Contribute during a phase of rapid growth as we focus on scaling models and improving platform performance
Help build backend systems, support client‑facing deployments, and enable smoother workflows for machine learning solutions
Develop and maintain AI/ML systems: Build robust, scalable backend systems that support machine learning operations and data processing pipelines
Cloud operations and management: Oversee and optimize cloud infrastructure to ensure efficient deployment and operation of ML models
Problem solving: Independently explore and address complex problem spaces to improve system capabilities and performance without extensive guidance
Cross‑functional collaboration: Work closely with ML engineers and data scientists to integrate advanced ML technologies, ensuring seamless operations across various platforms
Client engagement: Collaborate directly with Invisible’s clients, working embedded with client teams to support use case discovery, product development, and AI deployment
Innovation and R&D: Actively participate in research and development of new tools that can enhance our AI capabilities and workflows

Technologies

PythonAWSGCPAzureKubernetes

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