Founding AI Engineer (India)

fiska.AI; Itanagar; Remote; INR 350,000 - 750,000; Full time

Benefits offered by this job

Founding equity

Health insurance

Remote first

Flexible time off

Learning budget

Career growth

Job summary

Fiska is seeking a Founding AI Engineer to build production-grade AI systems powering our expense management platform. You will own the entire AI stack—from research to deployment—and shape how thousands of finance teams interact with financial data.

Join cofounders to implement agentic workflows, RAG pipelines, and scalable AI experiences with enterprise-grade reliability and security, while maintaining a strong customer-first focus.

Qualifications

• Proactive and self-motivated engineer with ownership mentality.
• Builder's mindset with rapid prototyping and user experience focus.
• Expertise in large language models through professional work or strong projects.
• Experience integrating multiple LLM providers with tool-calling and robust fallbacks.
• Hands-on with RAG systems including embeddings and reranking.
• Solid CS fundamentals and performance profiling.
• Advanced prompt engineering with libraries and failure analysis.
• Strong KPIs experience including designing A/B tests and human feedback.
• Production experience with MongoDB: schema design and scaling.
• Proficiency in Python with modern ML/AI frameworks.

Responsibilities

• Own agentic AI SMMP workflows from concept to production.
• Develop evaluation frameworks for prompts and models with offline/online testing.
• Build context management systems with RAG, memory, summarization, and data compression.
• Collaborate with founders to translate customer pain points into intelligent capabilities.
• Create reusable tools and SDKs to accelerate engineering teams.
• Manage integrations across multiple LLM providers with intelligent fallbacks.
• Implement observability dashboards tracking AI behavior, costs, and safety.
• Design safe and compliant AI outputs for financial data.
• Drive continuous improvement with metrics and A/B tests.

Skills

Proactive engineer

Builder mindset

LLM expertise

LLM integration

RAG systems

CS fundamentals

Prompt engineering

KPIs analysis

MongoDB experience

Python ML

Tools

Blueprints?

Job description

About Fiska

Fiska is transforming how finance teams manage event spend. We're building the first AI-powered platform that automates expense tracking, budget management, and real-time reconciliation for social media and marketing professionals (SMMPs).

About Fiska

Fiska is transforming how finance teams manage event spend. We're building the first AI-powered platform that automates expense tracking, budget management, and real-time reconciliation for social media and marketing professionals (SMMPs).

Our customers save an average of $250K+ annually and reduce reconciliation time by 78%. We're backed by leading investors and working with global brands to solve billion-dollar problems in event finance.

About The Role

As a Founding AI Engineer at Fiska, you'll be at the cutting edge of building production-grade AI systems that power our intelligent expense management platform. You'll own the entire AI stack—from research and experimentation to production deployment—and directly impact how thousands of finance teams interact with financial data.

This is a rare opportunity to shape the AI/ML direction of an early-stage startup, working directly with cofounders to build agentic systems, implement RAG pipelines, and create AI experiences that feel magical to users while maintaining enterprise-grade reliability and security.

Key Responsibilities

• Agentic Systems: Take agentic AI SMMP workflows from concept to production, owning the complete pipeline including retrieval, reasoning, tool integration, and safety measures while continuously improving accuracy through data-driven iteration
• Evaluation Infrastructure: Architect robust evaluation frameworks for prompts and models with both offline and online testing capabilities, enabling rapid experimentation through A/B testing and systematic performance comparison
• Context Engineering: Build sophisticated context management systems incorporating RAG, long-term memory, intelligent summarization, and data compression to enhance both conversations and automated expense categorization
• Product Collaboration: Partner directly with founders and product leaders to transform customer pain points into intelligent agent capabilities, run experiments, and deliver production features
• Internal Tools: Develop reusable tools and SDKs that empower engineering teams and AI systems to build faster, creating a multiplier effect across the organization
• Model Orchestration: Manage integrations across multiple LLM providers with intelligent fallback mechanisms, balancing cost efficiency, response speed, and output quality for optimal performance
• Observability: Implement comprehensive monitoring infrastructure tracking agent behavior, API costs, failure patterns, hallucination detection, and safety guardrails with actionable dashboards driving product strategy
• Safety & Compliance: Design and deploy robust guardrails, and implement safety protocols ensuring AI-generated outputs meet stringent financial industry compliance and regulatory requirements
• Continuous Improvement: Establish clear success metrics covering accuracy, latency, cost, and safety, design and execute A/B tests, and integrate user feedback loops to drive measurable quality improvements

Requirements

• Proactive and self-motivated engineer with strong ownership mentality and ability to drive projects independently from inception to completion
• Builder's mindset with comfort navigating ambiguity, rapid prototyping skills, systematic debugging approach, and relentless focus on user experience
• Demonstrated expertise in large language models through professional work or exceptional personal projects showcased on your resume
• Proven experience integrating multiple LLM providers with tool-calling and function-calling capabilities, comfortable switching between models and implementing robust fallback strategies
• Deep hands-on experience with RAG systems including indexing strategies, chunking techniques, embeddings, and reranking, with understanding of reliability and cost-latency optimization
• Solid computer science fundamentals including data structures, algorithms, comprehensive testing practices, and performance profiling
• Advanced prompt engineering skills with experience building prompt libraries, analyzing failure modes, and systematically refining prompts and policies
• Strong analytical ability to establish meaningful KPIs covering accuracy, latency, cost, and safety, with experience designing A/B tests and implementing human feedback systems
• Production experience with MongoDB including schema design, optimization, and scaling
• Proficiency in Python with hands-on experience in modern ML/AI frameworks and libraries

Nice to Have

• Working knowledge of cloud-native vector databases such as AWS OpenSearch with k-NN, Amazon MemoryDB for Redis, GCP Vertex AI Vector Search, pgvector on Aurora/AlloyDB, or managed services like Pinecone, Qdrant, or Weaviate
• Experience with AWS Bedrock Agents, GCP Vertex AI Agent Builder, or modern agent frameworks like LangGraph, CrewAI, and AutoGen for building production-grade agentic systems
• Hands-on experience with cloud AI platforms including AWS Bedrock, GCP Vertex AI, or Azure OpenAI for model deployment and orchestration
• Proficiency with LLM observability and evaluation platforms such as AWS CloudWatch with Bedrock integration, GCP Cloud Trace, Vertex AI Model Monitoring, Langfuse, Weights & Biases, or MLflow
• Experience with cloud-based fine-tuning and model optimization using AWS SageMaker, Amazon Bedrock Custom Models, GCP Vertex AI Training, or Model Garden
• Advanced understanding of retrieval systems, embeddings architecture, safety mechanisms, guardrail implementation, and red-team testing methodologies
• Academic or industry background in natural language processing or machine learning research with publications or patents

Benefits & Perks

Founding Team Package

Competitive salary aligned with top Indian startups plus significant equity stake to share in our growth

Health Insurance

Top-tier health insurance covering you and your family with major hospitals across India

Remote First

Work from anywhere in India with flexible hours and home office setup allowance

Flexible Time Off

Generous leave policy with paid time off, sick leave, and all Indian national holidays

Learning Budget

Annual learning allowance for AI/ML courses, certifications, research papers, and tech conferences

Career Growth

Early-stage startup with rapid growth opportunities and direct impact on company direction

Our Values

Customer First

Every decision starts with the customer. We obsess over solving real problems and delivering measurable value.

Fast & Agile

We move with speed and precision. Ship quickly, iterate constantly, and adapt to change.

Security First

We handle billions in event spend. Security and trust are non-negotiable in everything we build.

Own Your Work

We give you autonomy and trust you to make decisions. Take ownership and drive impact.

Sustainability

We build for the long term—sustainable growth, sustainable practices, sustainable impact.

Give Back

Success means lifting others. We invest in our communities and create opportunities for all.