Internal Applications & AI Platforms Engineer

Experience 2-3 years

Reports to IT Head

Location Onsite (in office)

Employment Full-time

About the role

We are hiring a hands-on engineer to own and evolve our internal product stacktools recruiters and HR use every day, plus the pipelines that connect them (ATS, telephony, call recording, and large language models). The role reports directly to the IT Head, ships fixes and features with minimal day-to-day supervision, and helps design and build new internal applications when the business needs them.

This is not a ticket-only maintenance role. The engineer will balance keeping Pluto, IRIS, Intake Recorder, and related services healthy with greenfield worksmall products, integrations, and AI-powered workflowsusing contemporary AI tools responsibly and effectively.

Products & environment (overview)

Pluto

AI recruiter co-pilot: job handbooks, resume scoring, screening, dashboards, Oorwin sync,Admin Tooling

IRIS:

Shared UI / design system and application shell across internal tools

Intake Recorder:

Call capture transcription handbook / job enrichment (extension, APIs, cloud storage

Typical stack:

Python (Flask), SQL databases, REST APIs, web front-ends, Git, Linux servers, environment-based configuration, background jobs.

AI: commercial LLM APIs, prompt design, evaluation, and knowing when not to use an LLM.

Key responsibilities:

Application ownership & reliability

- Monitor production and staging health; triage and fix issues without step-by-step direction.
- Deploy and roll back safely; document environments; run smoke checks after releases.
- Debug end-to-end flows (UI API database external APIs LLM calls).

Feature delivery

- Implement product requirements: screens, APIs, reports, admin tools, integration changes.
- Ship in small releases; write clear PR/commit notes; update docs when behaviour changes.

New builds





- Prototype and deliver new internal apps or modules (MVP iterate) from rough requirements.
- Reuse IRIS / Pluto patterns where appropriate; propose architecture for net-new apps.

AI & automation

- Use AI coding assistants and LLM APIs productively while maintaining quality and security.
- Understand limitations: hallucinations, PII, cost, latency, timeouts; follow data-handling norms.
- Improve prompts, fallbacks, and observability when AI features fail in production.

Stakeholder collaboration

- Work with recruiters, HR, and operations on bugs and enhancements; scope vague asks.
- Escalate on priority, security, or architecturenot on routine implementation.

Must have

- 23 years building and shipping web applications (backend-heavy or full-stack).
- Strong Python; comfort with SQL, REST APIs, and Git.
- Experience operating software in production (deploys, logs, incident debugging).
- Practical AI literacy: daily use of AI assistants; LLM API or AI-feature experience; can explain prompts and failure modes.
- Self-directed: plans work, asks focused questions, closes loops with minimal check-ins.
- Transparent written communication (email, Slack, short specs, release notes).

Nice to have

- Flask or similar Python web frameworks.
- Front-end basics (HTML, CSS, JavaScript, async APIs).
- Cloud storage, OAuth, webhooks, browser extensions.
- Recruitment / HR domain or ATS integrations.
- RAG, embeddings, or speech-to-text pipelines.
- Internal tools or single-tenant B2B-style applications.

Success in the first 6 months

- Confidently deploy and support Pluto and sibling apps; fix root causes, not only symptoms.
- Steady recruiter-visible improvements without daily task lists from the lead.
- At least one new requirement (feature or small app) from idea to production with light documentation.
- Faster delivery using AI tools with appropriate quality gates (no secrets in prompts, sensible errors).

📌 Internal Applications & AI Platforms Engineer (Bengaluru)
🏢 PeopleLogic Business Solutions
📍 Bengaluru