Lead Software Engineer

Location:

Remote (Work from Home)

About Forage AI: Forage AI delivers large-scale

data collection and processing platforms , including web crawlers, document parsers, data pipelines, AI/Agentic Solutions, and AI-assisted workflows. Our primary programming language is

Python . We design both cloud-native and cloud-agnostic solutions, primarily on

AWS , while also working with GCP and Azure. We value high ownership, strong collaboration, and pragmatic, well-documented engineering.

Role Overview (Engineering Lead, Hands-on): This is an Engineering Lead role with

strong hands-on

responsibilities. You will

lead

teams while

actively contributing to development . This includes reviewing designs and pull requests, pairing with engineers on complex problems, and setting technical direction. You are expected to stay deeply involved in architecture, development, and delivery, while also owning team execution, quality, and growth.

Key Responsibilities: Own

end‑to‑end delivery

of projects: requirements, scoping, design, implementation, testing, deployment, and operations. Architect

scalable, fault‑tolerant

systems for crawling, parsing, enrichment, and data processing. Write production code

in Python; set standards via

code reviews , design docs, and reference implementations. Mentor and grow engineers: coaching on design, coding best practices, observability, and operational excellence. Collaborate with stakeholders/clients: translate business needs into clear technical plans; manage risks and trade‑offs. Establish

engineering best practices

(branching strategy, CI/CD, testing strategy, security baselines, SLAs/SLOs, incident/RCA processes). Partner with QA/Ops to ensure quality gates, deployment hygiene, and on‑call readiness. Drive adoption and effective usage of

GenAI and AI-agent

systems. You are expected to have strong hands-on understanding of prompt engineering, agent design patterns, tool and function calling, RAG pipelines, evaluation techniques, and failure handling.

Required Qualifications: 7 to 11 years

of software engineering experience, with proven experience

leading engineering teams

and delivering projects end to end. Expert in

Python ; strong command over

data structures/algorithms , concurrency, and distributed systems concepts. Deep experience with

SQL

and

NoSQL

(plus schema design/modeling); familiarity with

vector databases . Proven track record designing and shipping

cloud‑native

systems on

AWS

(S3, Lambda, ECS/EKS, SQS/SNS, RDS/DynamoDB, CloudWatch, IAM). Significant experience building and operating

crawlers/parsers

and robust

ETL/ELT

pipelines. GenAI and LLM

experience, with hands-on exposure to LangChain, CrewAI, or LlamaIndex, prompt engineering, agent-based workflows, RAG pipelines, evaluation strategies, and quality controls. Hands-on experience with

CI/CD

and containerization, including GitHub Actions or Jenkins, Docker, and Kubernetes. Experience reviewing code, defining architecture, enforcing coding standards, and guiding teams toward scalable and maintainable designs. Strong proficiency with

Git, testing strategies

(unit, integration, and end-to-end), observability practices (logging, metrics, tracing), and performance tuning. Excellent communication: produces high‑quality design docs and gives actionable, empathetic feedback.

Preferred / Good to Have (Prioritized) Data Pipelines/Big Data :

Airflow ,

Spark ,

Kafka , or equivalents. Infra as Code & Cloud Ops : Terraform/CloudFormation; security hardening, cost/performance optimization, capacity planning. Frontend/JS :

not required ; basic JS or frontend exposure is

nice‑to‑have

only. Exposure to

GCP/Azure . Experience with interviewing, onboarding, and developing talent.

What Success Looks Like: Consistent delivery of well-designed, reliable systems with clear documentation and measurable reliability. Teams that ship high-quality code under your guidance, with junior engineers growing through active mentorship. Thoughtful technical decisions that balance delivery speed, cost, security, and long-term maintainability.

Work‑from‑Home Requirements: High‑speed internet for calls and collaboration. A capable, reliable computer ( modern CPU, 16GB+ RAM ). Headphones with clear audio quality. Stable power and backup arrangements.

Forage AI is an equal opportunity employer. We value curiosity, craftsmanship, and collaboration.