Role orientation: Senior hands-on individual contributor

Primary focus: End-to-end delivery of production AI solutions

Qualifications, work experience:

- Solution design. Work with product and business teams to convert a business workflow, decision or pain point into a practical AI solution and measurable acceptance criteria.
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- End-to-end engineering. Build complete small solutions, including the AI layer, backend services, data stores, APIs and a functional web interface where required.
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- AI workflow orchestration. Design reliable multi-step workflows involving foundation models, retrieval, machine-learning models, rules, external tools and human approvals.
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- Integration. Connect AI services with customer applications and enterprise systems using secure APIs, events or queues.
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- Production readiness. Implement testing, deployment, monitoring, fallback behaviour, audit logging and operational support for live customer use.
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- Performance and economics. Monitor latency, throughput, model usage and infrastructure cost; improve model selection, caching, batching and execution patterns.
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- Trust and control. Build explainability, confidence handling, human-in-the-loop review and traceable decision evidence into the workflow.
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- Technical leadership. Review the work of junior engineers, establish sound engineering patterns and make day-to-day technical decisions within the workstream.
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- Customer demonstrations. Demonstrate working solutions and answer technical questions clearly for customer stakeholders.
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- 5–7 years of software engineering, data/ML engineering or applied AI experience, including recent hands-on AI delivery.
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- Evidence that you personally built and deployed a live,



multi-step AI workflow in a regulated or control-sensitive setting, integrated with business systems and supported by human review and an audit trail.
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- Strong Python engineering skills and experience building production backend services and REST APIs using frameworks such as FastAPI, Flask or an equivalent.
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- Hands-on experience using commercial foundation-model APIs, structured outputs, tool/function calling, prompt design and systematic evaluation.
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- Practical experience with retrieval-augmented generation: document ingestion, chunking, embeddings, search/reranking, vector stores, citations and response-quality evaluation.
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- Working knowledge of conventional machine-learning development, including data preparation, feature engineering, model evaluation and safe handling of uncertain predictions.
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- Experience with SQL plus a non-relational or vector data store, with sound storage-design judgement.
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- Ability to build a basic web interface using React, Streamlit or a comparable framework.
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- Experience deploying containerised services on a major cloud platform using CI/CD, logging and monitoring.
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- A production mindset covering security, failure handling, retries, observability, versioning and maintainability.
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- Ability to work with limited or poorly labelled data and define realistic evaluation methods.
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- Clear written and verbal communication, including the ability to explain design choices, trade-offs and limitations during customer demonstrations.

Soft Skills:

- End-to-end ownership mindset
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- Strong documentation and communication
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- Comfortable with incident response and performance tuning

> Location: Bangalore

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> Work from Office.

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📌 Senior Software Engineer (Bengaluru)
🏢 iNube Software Solutions Private
📍 Bengaluru