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Lynx Analytics

AI Engineer (India)

  • Seen live on Lynx Analytics' site 2 days ago
  • Mid level
Pay
Not stated
Location
Pune, Maharashtra, India
Open for
12+ days
First seen
Oct 23, 2026

Posting record

No flags

Open 12+ days

The posting's record, oldest first
  1. Lynx Analytics' site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Lynx Analytics, so its true age is longer.

Last checked Nov 2, 2026.

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What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

We are expanding our agentic AI capability and are looking for an AI Engineer to join the team. You will work alongside senior engineers to build and maintain AI systems — contributing to agentic pipelines, retrieval infrastructure, and the integrations that tie these systems together.

This is a hands-on implementation role with real ownership of components. You will grow your skills in a fast-moving AI practice, working on production systems that directly affect client outcomes.

What This Involves

  • Build and maintain agentic pipelines and workflows under the guidance of senior engineers: tool use, orchestration, and multi-step reasoning.
  • Implement and tune RAG pipelines — including embedding, chunking strategies, vector retrieval, and retrieval evaluation.
  • Contribute to memory and context layer components: integrating vector databases, supporting knowledge graph pipelines, and helping maintain state management across agentic systems.
  • Write clean, well-tested Python code and participate in code reviews.
  • Debug and improve existing AI systems based on evaluation results and production feedback.
  • Collaborate with data engineers and domain experts to integrate AI components with upstream data sources and downstream applications.
  • Document implementations clearly and contribute to shared internal tooling.

Requirements

  • 2–4 years of software or ML engineering experience, with at least 1 year working with LLMs or AI systems in a professional setting.
  • Working knowledge of LLM APIs (OpenAI, Anthropic, or similar) and at least one agentic or RAG framework (LangChain, LlamaIndex, or equivalent).
  • Solid Python skills and comfort with software engineering basics: version control, testing, REST APIs.
  • Familiarity with vector databases or embedding-based search.
  • Curiosity about agentic AI — you follow developments in the space and are eager to apply new techniques.
  • Excellent communication and collaboration skills — comfortable working across cross-functional and client-facing teams.
  • Ability to overlap with Pacific Time business hours for a minimum of 3 hours per day.

Key Competencies

  • Stakeholder Mentality: Treats the company's and client’s goals as their own and is genuinely motivated by its success.
  • Organisational Excellence : Manages time and priorities effectively, ensuring tasks are completed accurately and on time even in a fast-paced environment.
  • Discretion & Integrity : Handles sensitive and confidential information with professionalism and sound judgement.
  • Problem Solving : Approaches challenges proactively and with a solution-oriented mindset, taking initiative rather than waiting to be directed.
  • Collaboration : A team player who builds strong working relationships and communicates effectively with colleagues across all levels.

Why You Will Love It Here

  • Work on real-world AI and advanced analytics solutions with measurable business impact.
  • Collaborate with a global team of engineers and data scientists.
  • Exposure to diverse industries, modern cloud platforms, and cutting-edge AI technologies.
  • A collaborative culture that values real outcomes.
  • Rapid learning opportunities and diverse challenges.
  • Flat organisational hierarchy with high visibility and accessibility to our leaders.

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