Senior Software Engineer Backend

About Pocket FM

At our core, we are an AI-powered entertainment company with a deeply human-first philosophy. We believe technology should amplify creativity. Our proprietary AI systems work alongside writers, voice artists, and creative teams to help stories scale globally, faster, smarter, and with cultural depth and emotional integrity intact.

Today, Pocket FM is home to a vibrant community of 250+ million listeners, 300,000+ creators, and 100,00+ audio series. With over 140 billion minutes streamed annually, we have emerged as one of the fastest-growing media-tech companies in the world, and we are just getting started. We operate at a massive global scale, but with a startup mindset: curious, fast-moving, and deeply owner-driven.

At Pocket FM, teams are encouraged to think boldly, move with intent, and build for long-term impact as we shape the future of audio-first storytelling worldwide

Role Overview:

We're looking for a Backend Engineer to join our AI/ML platform team. In this role, you'll work closely with experienced engineers to build and support backend services that power AI-driven features.

Key Responsibilities:

● Assist in developing and maintaining backend services, APIs, and microservices using

Python or Go.

● Support the implementation of AI based systems & solutions, including working with

LLMs(speech, text, image/video generation), embeddings, RAGs, vector databases.

● Build and optimize backend components that support AI-powered features at scale.

● Participate in code reviews, documentation, and CI/CD workflows and mentor juniors to

do so.

● Set standard practice for code quality and guardrails to ensure bug free and

maintainable codes

● Contribute to improving performance, reliability, and security of backend services.

● Integrate backend services with cloud infrastructure, databases, caching, and storage

systems.

● Collaborate with AI/ML engineers to integrate LLM APIs and support inference

workflows.

● Write clean, maintainable, and well-tested code following engineering best practices.

● Define and monitor GenAI metrics including latency, token consumption,

hallucination rates, retrieval quality.

Required Qualifications

● Bachelor's or Master's degree in Computer Science, Software Engineering, or a related

field.

● Experience with Python or Go through coursework, projects, or internships.

● Basic understanding of backend concepts such as APIs, databases, and microservices.

● Familiarity with backend frameworks like FastAPI, Flask, Gin, or Echo is a plus.

● Understanding of RESTful APIs; exposure to gRPC or GraphQL is helpful but not

required.

● Experience with databases and caching systems, including SQL (MySQL, PostgreSQL),

NoSQL (MongoDB, Cassandra, Scylla), and Redis for caching.

● Interest in AI systems, LLMs, and backend infrastructure.

● Strong problem-solving skills and eagerness to learn in a fast-paced environment.

Nice-to-Have Skills

● Exposure to vector databases (Pinecone, FAISS, Weaviate) or information retrieval

concepts.

● Familiarity with LLM APIs (OpenAI, Anthropic, etc.) through side projects or coursework.

● Experience using Docker or basic containerization concepts.

● Awareness of cloud platforms (AWS, GCP, or Azure) from labs or projects.

● Knowledge of CI/CD pipelines, monitoring, or observability tools (Prometheus, Grafana,

Datadog).

● Interest in AI orchestration frameworks such as LangChain or LlamaIndex.

● Hands-on experience with RAG, vector search, agentic systems, and LLM orchestration

frameworks.

● Strong understanding of distributed systems, caching, observability, and cloud-native

architectures.We're looking for a Backend Engineer to join our AI/ML platform team. In this role, you'll work closely

with experienced engineers to build and support backend services that power AI-driven features.

Key Responsibilities:

● Assist in developing and maintaining backend services, APIs, and microservices using

Python or Go.

● Support the implementation of AI based systems & solutions, including working with

LLMs(speech, text, image/video generation), embeddings, RAGs, vector databases.

● Build and optimize backend components that support AI-powered features at scale.

● Participate in code reviews, documentation, and CI/CD workflows and mentor juniors to

do so.

● Set standard practice for code quality and guardrails to ensure bug free and

maintainable codes

● Contribute to improving performance, reliability, and security of backend services.

● Integrate backend services with cloud infrastructure, databases, caching, and storage

systems.

● Collaborate with AI/ML engineers to integrate LLM APIs and support inference

workflows.

● Write clean, maintainable, and well-tested code following engineering best practices.

● Define and monitor GenAI metrics including latency, token consumption,

hallucination rates, retrieval quality.

Required Qualifications

● Bachelor's or Master's degree in Computer Science, Software Engineering, or a related

field.

● Experience with Python or Go through coursework, projects, or internships.

● Basic understanding of backend concepts such as APIs, databases, and microservices.

● Familiarity with backend frameworks like FastAPI, Flask, Gin, or Echo is a plus.

● Understanding of RESTful APIs; exposure to gRPC or GraphQL is helpful but not

required.

● Experience with databases and caching systems, including SQL (MySQL, PostgreSQL),

NoSQL (MongoDB, Cassandra, Scylla), and Redis for caching.

● Interest in AI systems, LLMs, and backend infrastructure.

● Strong problem-solving skills and eagerness to learn in a fast-paced environment.

Nice-to-Have Skills

● Exposure to vector databases (Pinecone, FAISS, Weaviate) or information retrieval

concepts.

● Familiarity with LLM APIs (OpenAI, Anthropic, etc.) through side projects or coursework.

● Experience using Docker or basic containerization concepts.

● Awareness of cloud platforms (AWS, GCP, or Azure) from labs or projects.

● Knowledge of CI/CD pipelines, monitoring, or observability tools (Prometheus, Grafana,

Datadog).

● Interest in AI orchestration frameworks such as LangChain or LlamaIndex.

● Hands-on experience with RAG, vector search, agentic systems, and LLM orchestration

frameworks.

● Strong understanding of distributed systems, caching, observability, and cloud-native

architectures.

You can get more updates, insights and everything behind the scenes at -https://xtra.pocketfm.com/