Senior Software Engineer (AI / ML)

As a Senior Software Engineer (AI and ML), you will play a key role in designing and building scalable AI-powered solutions from concept to production. You will take complete ownership of features and services, following a "You build it, you own it" approach. We're looking for engineers who are passionate about building production-grade AI solutions and delivering impactful customer experiences.
Responsibilities:
Architect, design, develop, test, deploy, monitor, and maintain end-to-end AI/ML services.
Own complete modules and features throughout their lifecycle, from development to production support.
Collaborate with cross-functional teams to ensure efficient project execution and deliver value to customers.
Align your team's technical vision and roadmap with the organization's target architecture.
Drive and contribute to complex, cross-functional initiatives involving multiple domains.
Integrate pre-trained machine learning and generative AI models (preferably on Google Cloud Platform) into production services.
Build scalable, reliable, and maintainable AI-powered applications following software engineering best practices.
Requirements:
5+ years of overall software engineering experience.
2+ years of hands-on experience as an AI/ML/LLM engineer.
AI and Generative AI:
Strong understanding of AI/ML and generative AI fundamentals, including Large Language Models (LLMs), Prompt Engineering, Context Engineering, LLM Inference, Embeddings, Vector Databases, and KV Caching.
Extensive experience integrating or building AI/ML/LLM-powered modules and services.
Programming and Machine Learning:
Strong proficiency in Python.
Hands-on experience with: Pandas, NumPy, Scikit-learn, LangChain, and/or LlamaIndex.
Experience with machine learning frameworks such as PyTorch, TensorFlow, and Keras.
Backend Development:
Hands-on experience developing APIs and backend services using FastAPI, Django, Flask, Databases.
Experience working with MySQL, MongoDB, Redis, and BigQuery (or equivalent data warehouse technologies).
Cloud and DevOps:
Experience with Google Cloud Platform (preferred) or AWS.
Hands-on experience building and maintaining CI/CD pipelines using GitHub Actions.
Experience deploying and managing production workloads in cloud environments.
Distributed Systems:
Experience working with event-driven architectures using technologies such as Kafka, RabbitMQ, and equivalent messaging systems.
Preferred Qualifications:
Experience building production-grade generative AI applications.
Strong understanding of scalable system design and microservices architecture.
Experience with model deployment, monitoring, and observability.
Ability to own features end-to-end and work independently.
Passion for emerging technologies in AI, machine learning, analytics, and digital experiences.
Excellent collaboration and communication skills.
Ideal Candidate:
The ideal candidate is a hands-on software engineer with strong backend development expertise and practical experience building and deploying AI/ML solutions in production.
They should be comfortable owning features end-to-end, collaborating across teams, and staying ahead of advancements in AI and generative AI technologies.

Experience
4-8 yrs