The Role
Build and operate production backend systems for AI-powered clinical products, including streaming audio, ASR, LLM document generation, agent orchestration, reliability, observability, evaluation, and scalable distributed services. Own systems from design through deployment and on-call, using Python, FastAPI, AWS, Kubernetes, Redis, and PostgreSQL while collaborating with product, clinical, and mobile teams.
Summary Generated by Built In
Backend Solution Engineer
Location: Bengaluru (onsite)
Experience: 4+ years
About Eka.care
Eka Care is a health AI company on a mission to make world-class clinical intelligence available to every doctor, patient, and healthcare enterprise.
We build the models, data infrastructure, and clinical workflows that turn everyday care — a consultation, a prescription, a lab report — into structured, interoperable health data, so that better decisions can be made at the point of care and across the enterprise, whether that is a hospital, a diagnostic lab, or an insurer. Our products — EkaScribe, EkaDoc, EkaAgents, EkaAPI's and EkaPHR — cover the full span of clinical, patient, and enterprise use cases, and plug into national digital health infrastructure such as India's Ayushman Bharat Digital Mission in India.
The role
We're looking for a strong backend and systems engineer who has hands-on exposure with AI. Engineering comes first and AI second. You'll design, build and own production systems that combine core engineering, streaming audio, LLMs and agents, and you'll run them at scale. You'll own features from design doc to production to on-call, and you'll ship fast without breaking things.
What you'll do
- Architect and build on EkaScribe's pipeline: streaming audio intake, ASR, transcript processing, LLM-based document generation, and the doctor's edit-and-publish loop. Low latency and high availability are requirements.
- Own reliability end to end: SLOs, fallbacks across model providers, retries, idempotency, backpressure, graceful degradation, incident response and postmortems.
- Build evals and observability for LLM systems: offline eval suites, online quality signals, hallucination and omission tracking, and LLM tracing. Every prompt or model change should ship with evidence that it's better.
- Build agentic systems: tool-using agents, multi-step orchestration, memory and retrieval, and guardrails that keep agents grounded in what was actually said and recorded.
- Design for scale and optimised solutions: queue-based async processing, caching, batching, token and GPU cost budgets, and multi-tenant isolation.
- Ship at a high pace: short iteration cycles, small safe deploys, feature flags, and clear written design docs.
- Work closely with product, clinical and mobile teams, and turn unclear clinical problems into well-scoped systems.
Must-have
- 4+ years building and running production backend systems, with a track record of owning services others depend on.
- Strong system design fundamentals: distributed systems, concurrency, consistency trade-offs, API design and data modelling.
- Strong exposure and adherence to system reliability principles
- High-speed delivery capability/ startup environment without compromising on reliability
- Hands-on with Python, Fast API, MCPs, Design Principles, AWS and Kubernetes: deploying, autoscaling and debugging services in production.
- Solid experience with Redis and Postgres: event-driven design, caching, and schema and query design at scale.
- Hands-on LLM application and agent experience in production: prompting, tool calling, structured outputs, RAG, and orchestration (LangGraph, CrewAI or custom).
- Experience building evals and observability for LLM systems: test sets, automated and LLM-as-judge scoring, tracing, and regression gates.
- A strong ownership mindset. You own it in production, not just on merge.
Nice-to-have
- Working knowledge of speech/ASR pipelines: streaming audio, ASR model trade-offs, diarization, and handling noisy, multilingual audio.
- Other languages / technology used for high-throughput services
- Vector search (pgvector or similar) and memory systems for agents
- Healthcare or regulated-data experience (ABDM, HIPAA, PII handling)
- Open-source contributions or public writing
Full-Time Employee Benefits:
• Insurance Benefits - Medical Insurance, Accidental Insurance
• Parental Support - Maternity Benefit, Paternity Benefit Program
• Retirement Benefits - Employee PF Contribution, Gratuity, NPS, Leave Encashment
• Other Benefits - Salary Advance Policy
Skills Required
- 4+ years building and running production backend systems
- Strong distributed systems, concurrency, consistency, API design, and data modeling fundamentals
- Experience applying system reliability principles
- Ability to deliver quickly in a startup environment without compromising reliability
- Hands-on experience with Python, FastAPI, MCPs, design principles, AWS, and Kubernetes
- Experience deploying, autoscaling, and debugging production services
- Experience with Redis and PostgreSQL, including event-driven design, caching, schema design, and query design at scale
- Production experience building LLM applications and agents, including prompting, tool calling, structured outputs, RAG, and orchestration
- Experience building LLM evaluations and observability, including test sets, automated scoring, LLM-as-judge scoring, tracing, and regression gates
- Strong ownership of production systems
- Working knowledge of speech and ASR pipelines, streaming audio, diarization, and noisy multilingual audio
- Experience with other languages or technologies for high-throughput services
- Experience with vector search such as pgvector or similar and agent memory systems
- Healthcare or regulated-data experience, including ABDM, HIPAA, or PII handling
- Open-source contributions or public writing
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The Company
What We Do
A digitally enabled and connected healthcare ecosystem for better health management. - Manage Your Health Records - Monitor Your Health Vitals - Easy To Use - Private And Secured - Govt. of India Approved #prioritizehealth
