Senior Software Engineer – Chat & Agent Systems

🕒 September 12

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 22%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Kantiv

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2022

🏗️ Construction

Construction

Kantiv is a software company that provides knowledge and pursuit intelligence tools for the Architecture, Engineering, and Construction (AEC) industry. Its product suite (including Kantiv Pursuit Intelligence, a Knowledge Graph, Image Management & Intelligence, and proposal-creation features) helps AEC firms capture and surface institutional knowledge, manage project imagery, and streamline creation of proposals and business-development materials. The website emphasizes solutions for proposal managers, marketing leaders, business development teams, and innovation leaders, and offers demos and enterprise-oriented workflows.

📋 Description

• Own the technical design and delivery of chat-team projects • Shape engineering priorities, standards, and day-to-day technical decisions • Translate product requirements into simple, maintainable system designs • Write production Python and remain involved in implementation • Design abstractions that reduce complexity without over-engineering • Review pull requests for correctness, maintainability, test coverage, and design quality • Guide junior developers through design guidance, code reviews, and mentoring • Diagnose production issues across application code, agent workflows, prompts, models, data, and infrastructure • Improve reliability, observability, latency, and cost of chat systems • Improve use of coding agents throughout the development lifecycle • Mentor engineers in planning, implementation, testing, debugging, and code-review workflows using coding agents • Lead initiatives that make the team faster and more AI-native

🎯 Requirements

• Approximately 4–5 years of professional software engineering experience • Strong proficiency in Python, including idiomatic, typed, testable, and maintainable production code • Strong programming fundamentals and sound engineering judgment • Experience designing, delivering, and operating production systems • Ability to create useful abstractions while keeping systems simple and understandable • Strong knowledge of API design, data modeling, concurrency, error handling, and observability • Experience writing effective automated tests with tools such as pytest • Ability to review code beyond surface-level concerns and explain suggested changes • Experience mentoring junior developers • Comfort taking ownership and driving team improvements • Clear written and verbal communication • Hands-on experience building LLM or agentic applications is required • Experience with tool-calling or multi-step workflows using LangGraph or comparable agent frameworks • Experience designing conversation state, context management, and execution flows • Experience with model APIs, structured outputs, retrieval, and grounding • Experience supporting streaming responses and asynchronous execution • Experience evaluating prompts, models, and end-to-end agent behavior • Experience with Langfuse, LangSmith, or similar observability platforms • Experience managing reliability, latency, and cost of production LLM systems • Power-user experience with agentic coding workflows across exploration, planning, implementation, testing, debugging, and review • Ability to provide coding agents with context, constraints, and verification steps • Ability to critically evaluate generated code for correctness, security, maintainability, and complexity • Ability to design development workflows that maintain accountability for resulting code • Ability to identify workflows improved through agents and automation • Ability to teach junior developers effective coding-agent use