Forward Deployed Engineer II, Transformation

Jobtailor; Bengaluru; On-site; INR 1,500,000 - 2,600,000; Full time

Job summary

Jobtailor in Bengaluru seeks a hands-on engineer to own customer solutions end-to-end, prototype rapidly, and deliver real value in live environments. You will be the technical face of the company, manage multiple engagements, set expectations, and drive changes with a bias to action.

Strong skills in Python, LLM‑based apps, data pipelines, and enterprise integrations are essential. You will collaborate across teams, read complex systems, and contribute to AI-enabled customer outcomes in

Qualifications

• 2–5 years of professional experience in software engineering, data engineering, solutions engineering, or a technical‑founder role.
• Prior exposure to customer‑facing technical roles — solutions engineering, forward deployment, technical consulting, or a startup where you wore multiple hats — is a strong signal, though not a requirement.
• Bias to action. Self‑directed. Always learning. Customer‑obsessed. Comfortable with ambiguity.

Responsibilities

• Own customer solutions end-to-end.
• Rapidly prototype, iterate, and deploy solutions in live operational environments where the stakes are real and the timeline is short.
• Deliver relentless customer value.
• Build trusted relationships from the IC level to the executive sponsor and become the technical face of our company in the room.
• Run multiple threads. Carry several customer engagements in parallel based on customer priorities and pod capacity.
• Set expectations early, renegotiate honestly when reality shifts, operate without close supervision, and own the outcome.
• Operate as a SEAL team. A small, tight, multi‑disciplinary unit with focus and urgency — tasks are traded seamlessly to whoever is closest to the skills needed.

Skills

Python

LLM‑Based Applications

REST APIs

Data Pipelines

Airflow

Kafka

Dbt

Data Modeling

Debugging

Integration with Enterprise Systems

Customer-Obsessed

Self-Directed

Comfortable with Ambiguity

Always Learning

Drives Change

Tools

Airflow

Kafka

dbt

Job description

Responsibilities

• Own customer solutions end-to-end.
• Rapidly prototype, iterate, and deploy solutions in live operational environments where the stakes are real and the timeline is short.
• Deliver relentless customer value.
• Build trusted relationships from the IC level to the executive sponsor and become the technical face of our company in the room.
• Run multiple threads. Carry several customer engagements in parallel based on customer priorities and pod capacity.
• Set expectations early, renegotiate honestly when reality shifts, operate without close supervision, and own the outcome.
• Operate as a SEAL team. A small, tight, multi‑disciplinary unit with focus and urgency — tasks are traded seamlessly to whoever is closest to the skills needed.

Requirements

• 2 – 5 years of professional experience in software engineering, data engineering, solutions engineering, or a technical‑founder role.
• Prior exposure to customer‑facing technical roles — solutions engineering, forward deployment, technical consulting, or a startup where you wore multiple hats — is a strong signal, though not a requirement.
• Bias to action.
• Self‑directed.
• Always learning.
• Customer‑obsessed.
• Comfortable with ambiguity.
• Drives change, not just code.
• Strong foundations in:
  • AI & Agentic Development: Hands‑on experience building LLM‑based applications — RAG systems, multi‑agent workflows, tool‑use patterns, prompt and context engineering. Familiarity with modern AI‑assisted development tools (Copilot, Claude Code, agentic IDE workflows) as daily practice, not novelty.
  • Software Engineering: Solid, hands‑on software engineering fundamentals: you have built and shipped real systems, not just scripts. Proficiency in at least one backend language (Python strongly preferred) and the ability to read and contribute across a polyglot codebase. Experience with REST and streaming APIs, authentication patterns, and integration with enterprise systems.
  • Data Engineering & Platforms: Ability to build and maintain data pipelines — ingestion, transformation, serving, and monitoring — using tools such as Airflow, Kafka, dbt, or equivalents. Working familiarity with modern data platforms (Snowflake, Databricks, BigQuery, or similar), including data modeling and performance fundamentals. Strong debugging instincts with imperfect, real‑world data in production environments.
  • Supply Chain Domain (Nice to Have): Prior exposure to supply chain planning, logistics, or operations domains is a genuine plus — not a requirement. Experience with or curiosity about platforms like Kinaxis, SAP IBP, o9, or Blue Yonder is welcome context.

Hard Skills

• Python
• LLM‑Based Applications
• REST APIs
• Data Pipelines
• Airflow
• Kafka
• Dbt
• Data Modeling
• Debugging
• Integration with Enterprise Systems

Soft Skills

• Customer‑Obsessed
• Self‑Directed
• Comfortable with Ambiguity
• Always LearningDrives Change