Senior Software Engineer - Prompt Engineering

SproutsAIChennai

5 days ago

Job description

Description : What you'll do :

Design & build production services and UIs, from APIs to frontends, with an eye for simplicity, performance, and operability.
Own systems instrument, monitor, and debug in prod; drive incident response and post-mortems; automate everything.
Evolve our AI stack prototype and productionize features that depend on LLMs - prompt pipelines, evals, guardrails, retrieval, and memory.
Tune & measure experiment with model selection,finetuning, quantization, LoRA,PEFT, structured outputs, function,tool calling, and latency,cost tradeoffs.
Ship great APIs design pragmatic REST, GraphQL, and,or gRPC interfaces; versioning, pagination, authN,Z, schema evolution, and backward compatibility.
Collaborate tightly with product,design to turn ambiguous problems into lovable, secure, and compliant experiences.
Mentor teammates via reviews, tech talks, and crisp docs.

What makes you a great fit :

Curiosity as a habit you read release notes, try new runtimes and models, and build weekend prototypes for fun, a lot of your Youtube consumption is hacking and learning new technologies, and you enjoy learning what you dont know on your own

Self-driven you find the problem behind the problem, align stakeholders, and land outcomes without hand-holding.

Systems mindset you think in SLOs, budgets (latency,cost,error), blast radius, and graceful degradation.

API ergonomics you care about naming, error design, rate limits, observability, generated SDKs, and docs that dont lie.

Data foundations you know when to pick Postgres vs columnar vs KV vs vector; you`ve shipped schema migrations and zero-downtime deploys.

LLM-practical you`ve built RAG or agents in anger; you understand context windows, tokenization, evals, and prompt,tooling hygiene.

Security instincts you default to least privilege, tame secrets, and design auth flows that survive real to have :

Hands-on with vector DBs (e. FAISS, HNSW, Milvus, PGVector), embeddings pipelines, and hybrid ranking.

Can Design retrieval layers build embeddings pipelines, vector indexes, hybrid search (BM25 + ANN), chunking,merging strategies, and memory graphs.

Protocol-fluent you actually enjoy HTTP,1.1 vs HTTP,2,3 quirks, caching semantics, content negotiation, and idempotency.

Experience with model hosting (self-hosted inference servers, serverless GPUs, or managed endpoints) and caching,streaming strategies.

Infra chops containers, IaC, CI,CD, service meshes, feature flags, canary,blue-green, cost observability.

Frontend XP with modern TypeScript frameworks and component systems; accessibility and performance budgets.

Prior startup experience or meaningful open-source contributions

(ref : hirist.tech)

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Senior Software Engineer • Chennai