Develop production-grade agentic AI applications in Python, including AI agents, multi-agent workflows, APIs, integrations, RAG pipelines, and cloud deployments. Use LLMs, vector databases, agent frameworks, and observability tools while implementing secure, governed AI solutions. Collaborate with clients, architects, product teams, and data scientists through workshops, demonstrations, proofs of concept, and troubleshooting sessions.
Software Engineering – Python – Advanced Role Overview
We are looking for an experienced Python Software Engineer to design, develop, and maintain scalable, high-performance software solutions. The ideal candidate should have strong hands-on expertise in Python development, backend engineering, API development, cloud technologies, and modern software engineering practices.
Key Responsibilities- Design, develop, test, and maintain scalable applications and backend services using Python.
- Build robust and reusable components, APIs, microservices, and integrations.
- Develop RESTful APIs and integrate with internal and external systems.
- Write clean, maintainable, well-tested, and production-ready code.
- Troubleshoot complex technical issues and optimize application performance.
- Work with databases, data models, caching, and asynchronous processing.
- Implement secure coding practices, authentication, authorization, and API security.
- Collaborate with Product Managers, Architects, DevOps, QA, and other engineering teams.
- Participate in code reviews, technical design discussions, and architecture decisions.
- Develop automated unit, integration, and functional tests.
- Work with CI/CD pipelines and modern DevOps practices.
- Monitor applications in production and support troubleshooting and root-cause analysis.
- Contribute to technical documentation and engineering best practices.
- Advanced proficiency in Python with strong knowledge of Python 3.x.
- Strong understanding of object-oriented programming, data structures, algorithms, and design patterns.
- Experience with Python frameworks such as FastAPI, Flask, or Django.
- Strong experience developing REST APIs and microservices.
- Good understanding of SQL and relational databases such as PostgreSQL, MySQL, or Oracle.
- Experience with NoSQL databases such as MongoDB, DynamoDB, or Redis is preferred.
- Strong knowledge of Git and version-control practices.
- Experience with unit testing frameworks such as PyTest or unittest.
- Knowledge of asynchronous programming using asyncio and related Python frameworks.
- Experience with Docker and containerized application development.
- Understanding of CI/CD and DevOps practices.
- Strong debugging, problem-solving, and performance-optimization skills.
- Experience working with at least one major cloud platform: AWS, Azure, or GCP.
- Understanding of cloud-native application development and distributed systems.
- Experience with messaging/event-driven technologies such as Kafka, RabbitMQ, or SQS is preferred.
- Familiarity with Kubernetes and container orchestration is a plus.
- Exposure to observability tools, logging, monitoring, and application performance management.
- Exposure to Generative AI, LLMs, or AI-enabled applications is preferred.
- Experience integrating LLM APIs or AI services into Python applications is a plus.
- Familiarity with frameworks such as LangChain, LangGraph, OpenAI SDK, or similar agentic AI frameworks is desirable.
- Understanding of API-based integration with AI/ML platforms and model-serving infrastructure is an advantage.
- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
- Typically 5+ years of software engineering experience, with strong hands-on Python development experience.
- Experience working in Agile/Scrum development environments.
- Strong communication and collaboration skills.
- Ability to independently analyze complex technical problems and deliver scalable solutions.
- Experience designing highly scalable distributed systems.
- Knowledge of system design and software architecture.
- Experience with event-driven and asynchronous architectures.
- Experience in financial services, enterprise applications, or other large-scale environments.
- Exposure to security, observability, and performance engineering.
Compensation, Benefits and Duration
Minimum Compensation: USD 42,000
Maximum Compensation: USD 147,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full-time employees.
This position is available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
Similar Jobs
Information Technology • Productivity • Software • Infrastructure as a Service (IaaS)
Develop scalable C++ software that defines and enforces endpoint behavior across millions of managed Windows endpoints. Responsibilities include implementing features, improving platform performance, shipping production code, designing new systems, writing architecture documents, defining subsystem contracts, and collaborating with server, UI, product, and design teams. The role requires deep Windows systems and kernel-driver expertise, with preferred experience in WHQL, minifilter or WFP drivers, macOS Endpoint Security, and Linux kernel development.
Top Skills:
AWSC++C++14+GoJavaKernel-Mode DriversKotlinLinux EbpfLinux Kernel ModulesMacos Endpoint SecurityMinifilterPostgresWhqlWindowsWindows Filtering Platform (Wfp)Windows Kernel Drivers
eCommerce • Information Technology • Retail • Industrial
Lead development of scalable search-platform software focused on product-catalog relevance. Design lexical and semantic retrieval, hybrid ranking, reranking, and learning-to-rank systems; evaluate quality through offline metrics and online experiments. Partner with Data Science, Product, Analytics, and Architecture teams on embeddings, relevance measurement, and technical solutions. Maintain production systems, resolve issues, mentor engineers, conduct code reviews, and promote continuous delivery and engineering best practices.
Top Skills:
AgileApproximate Nearest Neighbor (Ann) IndexingBm25CachingDevOpsDistributed SystemsEmbeddingsHybrid RetrievalIndexingJavaLearning-To-RankPythonQuery RoutingReplicationRerankingScrumSemantic SearchShardingTf-IdfVector Search
Cloud • Healthtech • Professional Services • Software • Pharmaceutical
Leads an eLearning team developing, maintaining, and optimizing self-paced digital learning content for a clinical data platform. Owns content strategy, roadmaps, production workflows, quality standards, analytics, accessibility, and learning outcomes. Collaborates with subject matter experts, product teams, stakeholders, and external partners to translate complex concepts into effective training. Uses AI and emerging technologies to improve development and personalization, while mentoring team members and incorporating learner feedback.
Top Skills:
ArticulateArtificial IntelligenceCamtasiaCaptivateData ReportingLearning Management SystemsMS Office
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
